Radio access network configuration for video approximate semantic communications

ABSTRACT

An apparatuses for radio access network configuration for video approximate semantic communications includes a transceiver that receives from a transmitter a bitstream corresponding to a video coded data transmission wherein the received bitstream includes bitwise transmission errors and a processor that performs FEC decoding and correcting at least one bitwise transmission error of the video coded data transmission whereas at least one bitwise transmission error is left in a bit-inexact reception of the video coded data transmissions post FEC decoding, applies, by a smart video decoder in a video approximate semantic communications mode, semantic error correction to decoded video coded data transmissions to correct and conceal one or more video artifacts in response to the bit-inexact reception of the video coded data transmissions post FEC decoding, and reconstructs a video uncoded representation of concealed approximate semantic content relative to the received bitstream corresponding to the video coded data transmission.

FIELD

The subject matter disclosed herein relates generally to wirelesscommunications and more particularly relates to radio access networkconfiguration for video approximate semantic communications.

BACKGROUND

In wireless networks, emerging applications such as augmented reality(“AR”)/virtual reality (“VR”)/extended reality (“XR”), cloud gaming(“CGM”), device remote tele-operation (e.g., vehicle tele-operation,robot arms tele-operation, or the like), 3D video conferencing, smartremote education, or the like are expected to drive increase in videotraffic. Even though the foregoing applications may require differentquantitative constraints and configurations in terms of rate,reliability, latency, and quality of service (“QoS”), it is expectedthat such constraint sets will challenge current and futurecommunications networks in delivering a high-fidelity quality ofexperience (“QoE”) at ever increasing resolutions. As the quality ofrendering end devices will increase and their costs will decrease withtime, such applications are expected to steadily expand and furthermorealso increase the bar on the QoE of end applications. As such it is ofhigh interest to provide scalable and reliable solutions from acommunications network perspective for the next generation media contentdelivery systems and their immersive digital reality applications.

BRIEF SUMMARY

Disclosed are procedures for radio access network configuration forvideo approximate semantic communications. Said procedures may beimplemented by apparatus, systems, methods, and/or computer programproducts.

In one embodiment, a first apparatus includes a transceiver thatreceives from a transmitter a bitstream corresponding to a video codeddata transmission wherein the received bitstream includes bitwisetransmission errors. In one embodiment, the first apparatus includes aprocessor that performs forward error correction (“FEC”) decoding andcorrecting at least one bitwise transmission error of the video codeddata transmission whereas at least one bitwise transmission error isleft in a bit-inexact reception of the video coded data transmissionspost FEC decoding. In one embodiment, the processor applies, by a smartvideo decoder in a video approximate semantic communications mode,semantic error correction to decoded video coded data transmissions tocorrect and conceal one or more video artifacts in response to thebit-inexact reception of the video coded data transmissions post FECdecoding. In one embodiment, the processor reconstructs a video uncodedrepresentation of concealed approximate semantic content relative to thereceived bitstream corresponding to the video coded data transmission.

In one embodiment, a first method includes receiving a bitstreamcorresponding to a video coded data transmission wherein the receivedbitstream from a transmitter includes bitwise transmission errors. Inone embodiment, the first method includes performing FEC decoding andcorrecting at least one bitwise transmission error of the video codeddata transmission whereas at least one bitwise transmission error isleft in a bit-inexact reception of the video coded data transmissionspost FEC decoding. In one embodiment, the first method includesapplying, by a smart video decoder in a video approximate semanticcommunications mode, semantic error correction to decoded video codeddata transmissions to correct and conceal one or more video artifacts inresponse to the bit-inexact reception of the video coded datatransmissions post FEC decoding. In one embodiment, the first methodincludes reconstructing a video uncoded representation of concealedapproximate semantic content relative to the received bitstreamcorresponding to the video coded data transmission.

In one embodiment, a second apparatus includes a transceiver thatreceives an indication of video approximate semantic communications modeof a receiver and a configuration thereof and transmits a plurality ofvideo coded data transmissions. In one embodiment, the second apparatusincludes a processor that uses the configuration of video approximatesemantic communications mode of the receiver to process hybrid automaticrepeat request (“HARQ”) feedback monitoring and to signal forenablement/disablement of semantic error correction at the receiver.

In one embodiment, a second method includes receiving an indication ofvideo approximate semantic communications mode of a receiver and aconfiguration thereof and transmitting a plurality of video coded datatransmissions. In one embodiment, the second method includes using theconfiguration of video approximate semantic communications mode of thereceiver to process HARQ feedback monitoring and to signal forenablement/disablement of semantic error correction at the receiver.

BRIEF DESCRIPTION OF THE DRAWINGS

A more particular description of the embodiments briefly described abovewill be rendered by reference to specific embodiments that areillustrated in the appended drawings. Understanding that these drawingsdepict only some embodiments and are not therefore to be considered tobe limiting of scope, the embodiments will be described and explainedwith additional specificity and detail through the use of theaccompanying drawings, in which:

FIG. 1 is a schematic block diagram illustrating one embodiment of awireless communication system for radio access network configuration forvideo approximate semantic communications;

FIG. 2 depicts a split-rendering architecture for mobile networks basedon an edge/cloud video application server and an XR UE device;

FIG. 3 depicts a simplified block diagram of a generic video codecperforming both spatial and temporal (motion) compression of a videosource;

FIG. 4 depicts one embodiment of a communications systems architectureoverview;

FIG. 5 depicts a comparison overview of current systems (top asbit-exact canonical communications systems) and the proposed system(bottom as video approximate semantic communications by semantic errorcorrection);

FIG. 6 depicts one embodiment of a smart video decoder with embeddedfunctionality for semantic error correction in support of videoapproximate semantic communications;

FIG. 7 depicts one embodiment of RAN level support for monitoring ofHARQ processes and retransmissions for gNB-assisted video approximatesemantic communications in DL;

FIG. 8 depicts one example of a CG retransmission timer update of CGautonomous retransmissions by means of explicit HARQ signaling as (NACK,SEC_ON) from a gNB receiver with semantic error correction in UL enabledvideo approximate semantic communications;

FIG. 9 is a block diagram illustrating one embodiment of a userequipment apparatus that may be used for radio access networkconfiguration for video approximate semantic communications;

FIG. 10 is a block diagram illustrating one embodiment of a networkapparatus that may be used for radio access network configuration forvideo approximate semantic communications;

FIG. 11 is a flowchart diagram illustrating one embodiment of a methodfor radio access network configuration for video approximate semanticcommunications; and

FIG. 12 is a flowchart diagram illustrating one embodiment of anothermethod for radio access network configuration for video approximatesemantic communications.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of theembodiments may be embodied as a system, apparatus, method, or programproduct. Accordingly, embodiments may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects.

For example, the disclosed embodiments may be implemented as a hardwarecircuit comprising custom very-large-scale integration (“VLSI”) circuitsor gate arrays, off-the-shelf semiconductors such as logic chips,transistors, or other discrete components. The disclosed embodiments mayalso be implemented in programmable hardware devices such as fieldprogrammable gate arrays, programmable array logic, programmable logicdevices, or the like. As another example, the disclosed embodiments mayinclude one or more physical or logical blocks of executable code whichmay, for instance, be organized as an object, procedure, or function.

Furthermore, embodiments may take the form of a program product embodiedin one or more computer readable storage devices storing machinereadable code, computer readable code, and/or program code, referredhereafter as code. The storage devices may be tangible, non-transitory,and/or non-transmission. The storage devices may not embody signals. Ina certain embodiment, the storage devices only employ signals foraccessing code.

Any combination of one or more computer readable medium may be utilized.The computer readable medium may be a computer readable storage medium.The computer readable storage medium may be a storage device storing thecode. The storage device may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, holographic,micromechanical, or semiconductor system, apparatus, or device, or anysuitable combination of the foregoing.

More specific examples (a non-exhaustive list) of the storage devicewould include the following: an electrical connection having one or morewires, a portable computer diskette, a hard disk, a random-access memory(“RAM”), a read-only memory (“ROM”), an erasable programmable read-onlymemory (“EPROM” or Flash memory), a portable compact disc read-onlymemory (“CD-ROM”), an optical storage device, a magnetic storage device,or any suitable combination of the foregoing. In the context of thisdocument, a computer readable storage medium may be any tangible mediumthat can contain or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

Code for carrying out operations for embodiments may be any number oflines and may be written in any combination of one or more programminglanguages including an object-oriented programming language such asPython, Ruby, Java, Smalltalk, C++, or the like, and conventionalprocedural programming languages, such as the “C” programming language,or the like, and/or machine languages such as assembly languages. Thecode may execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (“LAN”), wireless LAN (“WLAN”), or a wide areanetwork (“WAN”), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider(“ISP”)).

Furthermore, the described features, structures, or characteristics ofthe embodiments may be combined in any suitable manner. In the followingdescription, numerous specific details are provided, such as examples ofprogramming, software modules, user selections, network transactions,database queries, database structures, hardware modules, hardwarecircuits, hardware chips, etc., to provide a thorough understanding ofembodiments. One skilled in the relevant art will recognize, however,that embodiments may be practiced without one or more of the specificdetails, or with other methods, components, materials, and so forth. Inother instances, well-known structures, materials, or operations are notshown or described in detail to avoid obscuring aspects of anembodiment.

Reference throughout this specification to “one embodiment,” “anembodiment,” or similar language means that a particular feature,structure, or characteristic described in connection with the embodimentis included in at least one embodiment. Thus, appearances of the phrases“in one embodiment,” “in an embodiment,” and similar language throughoutthis specification may, but do not necessarily, all refer to the sameembodiment, but mean “one or more but not all embodiments” unlessexpressly specified otherwise. The terms “including,” “comprising,”“having,” and variations thereof mean “including but not limited to,”unless expressly specified otherwise. An enumerated listing of itemsdoes not imply that any or all of the items are mutually exclusive,unless expressly specified otherwise. The terms “a,” “an,” and “the”also refer to “one or more” unless expressly specified otherwise.

As used herein, a list with a conjunction of “and/or” includes anysingle item in the list or a combination of items in the list. Forexample, a list of A, B and/or C includes only A, only B, only C, acombination of A and B, a combination of B and C, a combination of A andC or a combination of A, B and C. As used herein, a list using theterminology “one or more of” includes any single item in the list or acombination of items in the list. For example, one or more of A, B and Cincludes only A, only B, only C, a combination of A and B, a combinationof B and C, a combination of A and C or a combination of A, B and C. Asused herein, a list using the terminology “one of includes one and onlyone of any single item in the list. For example, “one of A, B and C”includes only A, only B or only C and excludes combinations of A, B andC. As used herein, “a member selected from the group consisting of A, B,and C,” includes one and only one of A, B, or C, and excludescombinations of A, B, and C.” As used herein, “a member selected fromthe group consisting of A, B, and C and combinations thereof” includesonly A, only B, only C, a combination of A and B, a combination of B andC, a combination of A and C or a combination of A, B and C.

Aspects of the embodiments are described below with reference toschematic flowchart diagrams and/or schematic block diagrams of methods,apparatuses, systems, and program products according to embodiments. Itwill be understood that each block of the schematic flowchart diagramsand/or schematic block diagrams, and combinations of blocks in theschematic flowchart diagrams and/or schematic block diagrams, can beimplemented by code. This code may be provided to a processor of ageneral-purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart diagramsand/or block diagrams.

The code may also be stored in a storage device that can direct acomputer, other programmable data processing apparatus, or other devicesto function in a particular manner, such that the instructions stored inthe storage device produce an article of manufacture includinginstructions which implement the function/act specified in the flowchartdiagrams and/or block diagrams.

The code may also be loaded onto a computer, other programmable dataprocessing apparatus, or other devices to cause a series of operationalsteps to be performed on the computer, other programmable apparatus, orother devices to produce a computer implemented process such that thecode which execute on the computer or other programmable apparatusprovide processes for implementing the functions/acts specified in theflowchart diagrams and/or block diagrams.

The flowchart diagrams and/or block diagrams in the Figures illustratethe architecture, functionality, and operation of possibleimplementations of apparatuses, systems, methods, and program productsaccording to various embodiments. In this regard, each block in theflowchart diagrams and/or block diagrams may represent a module,segment, or portion of code, which includes one or more executableinstructions of the code for implementing the specified logicalfunction(s).

It should also be noted that, in some alternative implementations, thefunctions noted in the block may occur out of the order noted in theFigures. For example, two blocks shown in succession may, in fact, beexecuted substantially concurrently, or the blocks may sometimes beexecuted in the reverse order, depending upon the functionalityinvolved. Other steps and methods may be conceived that are equivalentin function, logic, or effect to one or more blocks, or portionsthereof, of the illustrated Figures.

Although various arrow types and line types may be employed in theflowchart and/or block diagrams, they are understood not to limit thescope of the corresponding embodiments. Indeed, some arrows or otherconnectors may be used to indicate only the logical flow of the depictedembodiment. For instance, an arrow may indicate a waiting or monitoringperiod of unspecified duration between enumerated steps of the depictedembodiment. It will also be noted that each block of the block diagramsand/or flowchart diagrams, and combinations of blocks in the blockdiagrams and/or flowchart diagrams, can be implemented by specialpurpose hardware-based systems that perform the specified functions oracts, or combinations of special purpose hardware and code.

The description of elements in each figure may refer to elements ofproceeding figures. Like numbers refer to like elements in all figures,including alternate embodiments of like elements.

Generally, the present disclosure describes systems, methods, andapparatus for radio access network configuration for video approximatesemantic communications. In certain embodiments, the methods may beperformed using computer code embedded on a computer-readable medium. Incertain embodiments, an apparatus or system may include acomputer-readable medium containing computer-readable code which, whenexecuted by a processor, causes the apparatus or system to perform atleast a portion of the below described solutions.

Emerging applications such as augmented reality (“AR”)/virtual reality(“VR”)/extended reality (“XR”), cloud gaming (“CGM”), device remotetele-operation (e.g., vehicle tele-operation, robot arms tele-operationetc.), 3D video conferencing, smart remote education, or the like areexpected to drive increase in video traffic. Even though the foregoingapplications may require different quantitative constraints andconfigurations in terms of rate, reliability, latency, and quality ofservice (“QoS”), it is expected that such constraint sets will challengecurrent and future communications networks in delivering a high-fidelityquality of experience (“QoE”) at ever increasing resolutions. As thequality of rendering end devices will increase and their costs willdecrease with time, such applications are expected to steadily expandand furthermore also increase the bar on the QoE of end applications. Assuch it is of high interest to provide scalable and reliable solutionsfrom a communications network perspective for the next generation mediacontent delivery systems and their immersive digital realityapplications.

Communications networks are one critical component of such applications.Another key technology in scaling the deployment of these immersivemedia experiences is the video encoding and compression of the sourcevideo information. This is critical in reducing the size of raw picturedata to a point where communications systems can reliably transmit thevideo content over various challenging network conditions associatedwith mobile and wireless data systems and applications. Currently, thecommunications plane is completely separated from the video sourceencoding plane which makes the optimization of transmission strategiesfor reliable QoE of such video intensive applications difficult and/orlimited. Despite current advances in video codec development (e.g.,H.266 standard release), the data increase rates of high resolutionmultiview/AR/XR/3D applications exceed the compression gains. As such,it is of interest to develop novel mechanisms to aid the communicationsand access networks to understand video codec knowledge bases andexploit the latter in designing and configuring optimized transmissionstrategies for the mentioned video applications.

In one embodiment, this disclosure proposes a method for videoapproximate semantic communications that includes a processing modelwherein a video codec specification represents a common fixed knowledgebase at a transmitter and at a receiver that allows bit inexactcommunications at the Physical Layer (“PHY”) transport level inopposition to conventional systems requiring bit exact transmissions, asmart video decoder as a semantic decoder composed of two jointfunctionalities encompassing the conventional video decoding and errorconcealment as a first operation and a second semantic error correctiongiven by artificial intelligence (“AI”)/machine learning (“ML”) learnedstatistical models or non-learned machine vision statistical methods forapproximate semantic reconstruction of bit inexact video codedtransmitted data, an end-to-end (“E2E”) communications pipelineintegrating said semantic processing to allow for bit inexact videocoded transmissions wherein PHY transport errors are mitigated andconcealed at a semantic level, and associated radio access network(“RAN”) level signaling to support video approximate semanticcommunications including user equipment (“UE”)/smart video decodercapabilities, hybrid automatic repeat request (“HARQ”) feedbackmechanism, RAN configuration and control signaling.

FIG. 1 depicts a wireless communication system 100 for radio accessnetwork configuration for video approximate semantic communications,according to embodiments of the disclosure. In one embodiment, thewireless communication system 100 includes at least one remote unit 105,a Fifth-Generation Radio Access Network (“5G-RAN”) 115, and a mobilecore network 140. The 5G-RAN 115 and the mobile core network 140 form amobile communication network. The 5G-RAN 115 may be composed of a ThirdGeneration Partnership Project (“3GPP”) access network 120 containing atleast one cellular base unit 121 and/or a non-3GPP access network 130containing at least one access point 131. The remote unit 105communicates with the 3GPP access network 120 using 3GPP communicationlinks 123 and/or communicates with the non-3GPP access network 130 usingnon-3GPP communication links 133. Even though a specific number ofremote units 105, 3GPP access networks 120, cellular base units 121,3GPP communication links 123, non-3GPP access networks 130, accesspoints 131, non-3GPP communication links 133, and mobile core networks140 are depicted in FIG. 1 , one of skill in the art will recognize thatany number of remote units 105, 3GPP access networks 120, cellular baseunits 121, 3GPP communication links 123, non-3GPP access networks 130,access points 131, non-3GPP communication links 133, and mobile corenetworks 140 may be included in the wireless communication system 100.

In one implementation, the RAN 120 is compliant with the 5G systemspecified in the 3GPP specifications. For example, the RAN 120 may be aNextGen RAN (“NG-RAN”), implementing New Radio (“NR”) Radio AccessTechnology (“RAT”) and/or Long Term Evolution (“LTE”) RAT. In anotherexample, the RAN 120 may include non-3GPP RAT (e.g., Wi-Fi® or Instituteof Electrical and Electronics Engineers (“IEEE”) 802.11-family compliantWLAN). In another implementation, the RAN 120 is compliant with the LTEsystem specified in the 3GPP specifications. More generally, however,the wireless communication system 100 may implement some other open orproprietary communication network, for example WorldwideInteroperability for Microwave Access (“WiMAX”) or IEEE 802.16-familystandards, among other networks. The present disclosure is not intendedto be limited to the implementation of any particular wirelesscommunication system architecture or protocol.

In one embodiment, the remote units 105 may include computing devices,such as desktop computers, laptop computers, personal digital assistants(“PDAs”), tablet computers, smart phones, smart televisions (e.g.,televisions connected to the Internet), smart appliances (e.g.,appliances connected to the Internet), set-top boxes, game consoles,security systems (including security cameras), vehicle on-boardcomputers, network devices (e.g., routers, switches, modems), or thelike. In some embodiments, the remote units 105 include wearabledevices, such as smart watches, fitness bands, optical head-mounteddisplays, or the like. In one embodiment, the remote unites 105 includedevices for presenting virtual reality environments, augmented realityenvironments, and/or extended reality environments, e.g., head-mounteddisplay units.

Moreover, the remote units 105 may be referred to as User Equipment(“UE”) devices, subscriber units, mobiles, mobile stations, users,terminals, mobile terminals, fixed terminals, subscriber stations, userterminals, wireless transmit/receive unit (“WTRU”), a device, or byother terminology used in the art. In various embodiments, the remoteunit 105 includes a subscriber identity and/or identification module(“SIM”) and the mobile equipment (“ME”) providing mobile terminationfunctions (e.g., radio transmission, handover, speech encoding anddecoding, error detection and correction, signaling and access to theSIM). In certain embodiments, the remote unit 105 may include a terminalequipment (“TE”) and/or be embedded in an appliance or device (e.g., acomputing device, as described above).

The remote units 105 may communicate directly with one or more of thecellular base units 121 in the 3GPP access network 120 via uplink (“UL”)and downlink (“DL”) communication signals. Furthermore, the UL and DLcommunication signals may be carried over the 3GPP communication links123. Similarly, the remote units 105 may communicate with one or moreaccess points 131 in the non-3GPP access network(s) 130 via UL and DLcommunication signals carried over the non-3GPP communication links 133.Here, the access networks 120 and 130 are intermediate networks thatprovide the remote units 105 with access to the mobile core network 140.

In some embodiments, the remote units 105 communicate with a remote host(e.g., in the data network 150 or in the data network 160) via a networkconnection with the mobile core network 140. For example, an application107 (e.g., web browser, media client, telephone and/orVoice-over-Internet-Protocol (“VoIP”) application) in a remote unit 105may trigger the remote unit 105 to establish a protocol data unit(“PDU”) session (or other data connection) with the mobile core network140 via the 5G-RAN 115 (e.g., via the 3GPP access network 120 and/ornon-3GPP network 130). The mobile core network 140 then relays trafficbetween the remote unit 105 and the remote host using the PDU session.The PDU session represents a logical connection between the remote unit105 and a User Plane Function (“UPF”) 141.

In order to establish the PDU session (or Packet Data Network (“PDN”)connection), the remote unit 105 must be registered with the mobile corenetwork 140 (also referred to as “attached to the mobile core network”in the context of a Fourth Generation (“4G”) system). Note that theremote unit 105 may establish one or more PDU sessions (or other dataconnections) with the mobile core network 140. As such, the remote unit105 may have at least one PDU session for communicating with the packetdata network 150. Additionally—or alternatively—the remote unit 105 mayhave at least one PDU session for communicating with the packet datanetwork 160. The remote unit 105 may establish additional PDU sessionsfor communicating with other data networks and/or other communicationpeers.

In the context of a 5G system (“5GS”), the term “PDU Session” refers toa data connection that provides E2E user plane (“UP”) connectivitybetween the remote unit 105 and a specific Data Network (“DN”) throughthe UPF 141. A PDU Session supports one or more QoS Flows. In certainembodiments, there may be a one-to-one mapping between a QoS Flow and aQoS profile, such that all packets belonging to a specific QoS Flow havethe same 5G QoS Identifier (“5QI”).

In the context of a 4G/LTE system, such as the Evolved Packet System(“EPS”), a PDN connection (also referred to as EPS session) provides E2EUP connectivity between the remote unit and a PDN. The PDN connectivityprocedure establishes an EPS Bearer, e.g., a tunnel between the remoteunit 105 and a Packet Gateway (“P-GW”), not shown, in an Evolved PacketCore Network (“EPC”). In certain embodiments, there is a one-to-onemapping between an EPS Bearer and a QoS profile, such that all packetsbelonging to a specific EPS Bearer have the same QoS Class Identifier(“QCI”).

As described in greater detail below, the remote unit 105 may use afirst data connection (e.g., PDU Session) established with a firstmobile core network, an EPC (not shown), to establish a second dataconnection (e.g., part of a second PDU session) with a second mobilecore network 140. When establishing a data connection (e.g., PDUsession) with the second mobile core network 140, the remote unit 105uses the first data connection to register with the second mobile corenetwork 140.

The cellular base units 121 may be distributed over a geographic region.In certain embodiments, a cellular base unit 121 may also be referred toas an access terminal, a base, a base station, a Node-B (“NB”), anEvolved Node B (abbreviated as eNodeB or “eNB,” also known as EvolvedUniversal Terrestrial Radio Access Network (“E-UTRAN”) Node B), a 5G/NRNode B (“gNB”), a Home Node-B, a relay node, a device, or by any otherterminology used in the art. The cellular base units 121 are generallypart of a RAN, such as the 3GPP access network 120, that may include oneor more controllers communicably coupled to one or more correspondingcellular base units 121. These and other elements of radio accessnetwork are not illustrated but are well known generally by those havingordinary skill in the art. The cellular base units 121 connect to themobile core network 140 via the 3GPP access network 120.

The cellular base units 121 may serve a number of remote units 105within a serving area, for example, a cell or a cell sector, via a 3GPPwireless communication link 123. The cellular base units 121 maycommunicate directly with one or more of the remote units 105 viacommunication signals. Generally, the cellular base units 121 transmitDL communication signals to serve the remote units 105 in the time,frequency, and/or spatial domain. Furthermore, the DL communicationsignals may be carried over the 3GPP communication links 123. The 3GPPcommunication links 123 may be any suitable carrier in licensed orunlicensed radio spectrum. The 3GPP communication links 123 facilitatecommunication between one or more of the remote units 105 and/or one ormore of the cellular base units 121. Note that during NR operation onunlicensed spectrum (referred to as “NR-U”), the base unit 121 and theremote unit 105 communicate over unlicensed (e.g., shared) radiospectrum.

The non-3GPP access networks 130 may be distributed over a geographicregion. Each non-3GPP access network 130 may serve a number of remoteunits 105 within a serving area. An access point 131 in a non-3GPPaccess network 130 may communicate directly with one or more remoteunits 105 by receiving UL communication signals and transmitting DLcommunication signals to serve the remote units 105 in the time,frequency, and/or spatial domain. Both DL and UL communication signalsare carried over the non-3GPP communication links 133. The 3GPPcommunication links 123 and non-3GPP communication links 133 may employdifferent frequencies and/or different communication protocols. Invarious embodiments, an access point 131 may communicate usingunlicensed radio spectrum. The mobile core network 140 may provideservices to a remote unit 105 via the non-3GPP access networks 130, asdescribed in greater detail herein.

In some embodiments, a non-3GPP access network 130 connects to themobile core network 140 via an interworking entity 135. The interworkingentity 135 provides an interworking between the non-3GPP access network130 and the mobile core network 140. The interworking entity 135supports connectivity via the “N2” and “N3” interfaces. As depicted,both the 3GPP access network 120 and the interworking entity 135communicate with the Access and Mobility Management Function (“AMF”) 143using a “N2” interface. The 3GPP access network 120 and interworkingentity 135 also communicate with the UPF 141 using a “N3” interface.While depicted as outside the mobile core network 140, in otherembodiments the interworking entity 135 may be a part of the corenetwork. While depicted as outside the non-3GPP RAN 130, in otherembodiments the interworking entity 135 may be a part of the non-3GPPRAN 130.

In certain embodiments, a non-3GPP access network 130 may be controlledby an operator of the mobile core network 140 and may have direct accessto the mobile core network 140. Such a non-3GPP AN deployment isreferred to as a “trusted non-3GPP access network.” A non-3GPP accessnetwork 130 is considered as “trusted” when it is operated by the 3GPPoperator, or a trusted partner, and supports certain security features,such as strong air-interface encryption. In contrast, a non-3GPP ANdeployment that is not controlled by an operator (or trusted partner) ofthe mobile core network 140, does not have direct access to the mobilecore network 140, or does not support the certain security features isreferred to as a “non-trusted” non-3GPP access network. An interworkingentity 135 deployed in a trusted non-3GPP access network 130 may bereferred to herein as a Trusted Network Gateway Function (“TNGF”). Aninterworking entity 135 deployed in a non-trusted non-3GPP accessnetwork 130 may be referred to herein as a non-3GPP interworkingfunction (“N3IWF”). While depicted as a part of the non-3GPP accessnetwork 130, in some embodiments the N3IWF may be a part of the mobilecore network 140 or may be located in the data network 150.

In one embodiment, the mobile core network 140 is a 5G core (“5GC”) oran EPC, which may be coupled to a data network 150, like the Internetand private data networks, among other data networks. A remote unit 105may have a subscription or other account with the mobile core network140. Each mobile core network 140 belongs to a single public land mobilenetwork (“PLMN”). The present disclosure is not intended to be limitedto the implementation of any particular wireless communication systemarchitecture or protocol.

The mobile core network 140 includes several network functions (“NFs”).As depicted, the mobile core network 140 includes at least one UPF 141.The mobile core network 140 also includes multiple control planefunctions including, but not limited to, an AMF 143 that serves the5G-RAN 115, a Session Management Function (“SMF”) 145, a Policy ControlFunction (“PCF”) 147, an Authentication Server Function (“AUSF”) 148, aUnified Data Management (“UDM”) and Unified Data Repository function(“UDR”).

The UPF(s) 141 is responsible for packet routing and forwarding, packetinspection, QoS handling, and external PDU session for interconnectingData Network (“DN”), in the 5G architecture. The AMF 143 is responsiblefor termination of Non-Access Stratum (“NAS”) signaling, NAS ciphering &integrity protection, registration management, connection management,mobility management, access authentication and authorization, securitycontext management. The SMF 145 is responsible for session management(e.g., session establishment, modification, release), remote unit (e.g.,UE) Internet Protocol (“IP”) address allocation & management, DL datanotification, and traffic steering configuration for UPF for propertraffic routing.

The PCF 147 is responsible for unified policy framework, providingpolicy rules to Control Plane (“CP”) functions, access subscriptioninformation for policy decisions in UDR. The AUSF 148 acts as anauthentication server.

The UDM is responsible for generation of Authentication and KeyAgreement (“AKA”) credentials, user identification handling, accessauthorization, subscription management. The UDR is a repository ofsubscriber information and can be used to service a number of networkfunctions. For example, the UDR may store subscription data,policy-related data, subscriber-related data that is permitted to beexposed to third party applications, and the like. In some embodiments,the UDM is co-located with the UDR, depicted as combined entity“UDM/UDR” 149.

In various embodiments, the mobile core network 140 may also include anNetwork Exposure Function (“NEF”) (which is responsible for makingnetwork data and resources easily accessible to customers and networkpartners, e.g., via one or more Application Programming Interfaces(“APIs”)), a Network Repository Function (“NRF”) (which provides NFservice registration and discovery, enabling NFs to identify appropriateservices in one another and communicate with each other over APIs), orother NFs defined for the 5GC. In certain embodiments, the mobile corenetwork 140 may include an authentication, authorization, and accounting(“AAA”) server.

In various embodiments, the mobile core network 140 supports differenttypes of mobile data connections and different types of network slices,wherein each mobile data connection utilizes a specific network slice.Here, a “network slice” refers to a portion of the mobile core network140 optimized for a certain traffic type or communication service. Anetwork instance may be identified by a single Network Slice SelectionAssistance Information (“S-NSSAI”), while a set of network slices forwhich the remote unit 105 is authorized to use is identified by NSSAI.In certain embodiments, the various network slices may include separateinstances of network functions, such as the SMF and UPF 141. In someembodiments, the different network slices may share some common networkfunctions, such as the AMF 143. The different network slices are notshown in FIG. 1 for ease of illustration, but their support is assumed.

In one embodiment, the network 100 includes an application server 142that hosts applications for use by the mobile network 140, the RAN 115,the remote unit 105, and/or the like. As it relates to the subjectmatter disclosed herein, the application server 142 may host a videocodec-aware application that is used to determine and indicate animportance of an underlying NAL unit of video coded elementary stream.The importance indicator may also be placed within the mobile network140 (e.g., at the UPF 141), the RAN 115 (e.g., at the upper layers),and/or the like.

Although specific numbers and types of network functions are depicted inFIG. 1 , one of skill in the art will recognize that any number and typeof network functions may be included in the mobile core network 140.Moreover, where the mobile core network 140 comprises an EPC, thedepicted network functions may be replaced with appropriate EPCentities, such as a Mobility Management Entity (“MME”), Serving Gateway(“S-GW”), P-GW, Home Subscriber Server (“HSS”), and the like.

While FIG. 1 depicts components of a 5G RAN and a 5G core network, thedescribed embodiments for using a pseudonym for access authenticationover non-3GPP access apply to other types of communication networks andRATs, including IEEE 802.11 variants, GSM, GPRS, UMTS, LTE variants,CDMA 2000, Bluetooth, ZigBee, Sigfox, and the like. For example, in an4G/LTE variant involving an EPC, the AMF 143 may be mapped to an MME,the SMF mapped to a control plane portion of a P-GW and/or to an MME,the UPF 141 may be mapped to an S-GW and a user plane portion of theP-GW, the UDM/UDR 149 may be mapped to an HSS, etc.

As depicted, a remote unit 105 (e.g., a UE) may connect to the mobilecore network (e.g., to a 5G mobile communication network) via two typesof accesses: (1) via 3GPP access network 120 and (2) via a non-3GPPaccess network 130. The first type of access (e.g., 3GPP access network120) uses a 3GPP-defined type of wireless communication (e.g., NG-RAN)and the second type of access (e.g., non-3GPP access network 130) uses anon-3GPP-defined type of wireless communication (e.g., WLAN). The 5G-RAN115 refers to any type of 5G access network that can provide access tothe mobile core network 140, including the 3GPP access network 120 andthe non-3GPP access network 130.

As background, a common setup adopted at the 3GPP level, e.g., 3GPPTechnical Report TR 26.928 (v16.0.0—November 2020). 5G; Extended Reality(XR) in 5G; S4-211210: [FS_XRTraffic]: Permanent document, v0.8.0,Rapporteur Qualcomm Inc., (2021), for immersive XR and high-performancevideo content transmissions relies on the concept of split rendering.This uses an application server located at the edge and connected to acore network (“CN”), which is used to encode the application videocontent and transfer it to a RAN for mobile communications. In exchange,the RAN communicates with a connected UE, which may use additionalhardware/software processing to render the video content to match auser's pose/inputs/control state. This architectural approach isdisplayed for reference in FIG. 2 .

FIG. 2 depicts a split-rendering architecture for mobile networks basedon an edge/cloud video application server and an XR UE device 203. Thedevice 203 is connected to a radio access network 208, which is in turnconnected to the application server 202 via a core network 205. Theapplication server 202 may deliver XR media based on local XR processedcontent or on remote XR processed content. The processing may accountfor and/or further process tracking and sensing information as uplinkedby the XR UE device 203. The application server 202 streams the XRmultimedia content via a content delivery gateway 210 to which the XR UEdevice 203 is connected via any real-time transport protocol. The XRdevice 203, after decoding the XR content received from the applicationserver 202, may use its XR engine 212 and additional localhardware/software capabilities and/or XR pre-rendered content, and XRassociated XR metadata to locally render the XR content on a display.

In the depicted embodiment, the video application server 202 is usedtherefore to process, encode, transcode, and/or serve local 204 orremote 206 video content pertaining to an AR/XR/CGM/tele-operationapplication session to the XR UE 203. The video application server 202may, as a result, encode/transcode and control the video viewportcontent and transmit it in downlink to the RAN 208 based on UE specificparameters, configurations and sensing inputs that may affect therendering perspective, rate, quality, panning, etc. This generalarchitecture is expected to leverage the advantages of various computeand network domains (e.g., cloud, edge, smart handsets/headsets) toenable scalable AR/XR/CGM/tele-operation applications and use cases withlow-latency, high rate, and efficient energy usage. The architecture isas such universally applicable both to split rendering with asynchronoustime warping devices, e.g., where the video application server encodes arasterized pre-processed viewport representation to aid the UE, or tosplit rendering with viewport rendering at the device side, e.g., wherethe video viewport may be completely or partially rendered at the deviceside given the media encoded video content and its correspondingmetadata available.

In one embodiment, related to video coding domain, the interactivityinvolving these applications requires guarantees in terms of meetingpacket error rate (“PER”) and packet delay budget (“PDB”) for the QoE ofrendering the associated video streams at a UE. The video source jitterand wireless channel stochastic characteristics of mobile communicationssystems make the former challenging to meet especially for high-ratespecific digital video transmissions, e.g., 4K, 3D video, 2×2Keye-buffered video, and/or the like.

In one embodiment, current video source information is encoded based on2D representations of video content. The encoded elementary stream videocontent is generally, regardless of the source encoder, organized intotwo abstraction layers meant to separate the storage and video codingdomains, e.g., the network abstraction layer (“NAL”), and the videocoding layer (“VCL”), respectively. The NAL syntax encapsulates the VCLinformation and provides abstract containerization mechanisms forin-transit coded streams, e.g., for disk storage/caching/transmissionand/or parsing/decoding.

The VCL, on the other hand, encapsulates the video coding procedures ofan encoder and compresses the source encoded video information based onsome entropy coding method, e.g., context-adaptive binary arithmeticencoding (“CABAC”), context-adaptive variable-length coding (“CAVLC”),and/or the like. A simplified description of the VCL procedures togenerically encode video content is as follows: a picture 302 in a videosequence is partitioned 304 into coding units (e.g., macroblocks, codingtree units or variations thereof) of a configured size. The coding unitsmay be subsequently split under some tree partitioning structures (seeITU-T Series H: Audiovisual and Multimedia Systems: Infrastructure ofAudiovisual Services-Coding of Moving video. Advanced Video Coding forGeneric Audiovisual Services (H.264) (v08/2021); ITU-T Series H:Audiovisual and Multimedia Systems: Infrastructure of AudiovisualServices-Coding of Moving video. High Efficiency Video Coding (H.265)(v08/2021); ITU-T Series H: Audiovisual and Multimedia Systems:Infrastructure of Audiovisual Services-Coding of Moving video. VersatileVideo Coding (H.266) (v08/2020)), e.g., binary/ternary/quaternary trees,or under some predetermined geometrically motivated 2D segmentationpatterns (see de Rivaz, P., & Haughton, J. (2018). AV1 Bitstream &Decoding Process Specification. The Alliance for Open Media, 182,available at https://aomediacodec.github.io/av1-spec/av1-spec.pdf),e.g., the 10-way split.

In one embodiment, encoders use visual references among such codingunits to encode picture content in a differential manner based onresiduals. The residuals are determined given the prediction modesassociated with the reconstruction of information. Two modes ofprediction are universally available as intra-prediction 306 (shortlyreferred to as intra as well) or inter-prediction 308 (or inter in shortform). The intra mode is based on deriving and predicting residualsbased on other coding units' contents within the current picture, e.g.,by computing residuals of current coding units given their adjacentcoding units coded content. The inter mode is based, on the other hand,on deriving and predicting residuals based on coding units' contentsfrom other pictures, e.g., by computing residuals of current codingunits given their adjacent coded pictures content.

The residuals are then further transformed for compression using somemulti-dimensional (2D/3D) spatial multimodal transform 310, e.g.,frequency-based, or wavelet-based linear transform, to extract the mostprominent frequency components of the coding units' residuals. Theinsignificant high-frequency contributions of residuals are dropped, andthe floating-point transformed representation of remaining residuals isfurther quantized 312 based on some parametric quantization proceduredown to a selected number of bits per sample, e.g., 8/10/12 bits.Lastly, the transformed and quantized residuals and their associatedmotion vectors to their prediction references either in intra or intermode are encoded using an entropy encoding mechanism to compress theinformation based on the stochastic distribution of the source bitcontent. The output of this operation is a bitstream 316 of the codedresidual content of the VCL. A simplified generic diagram of the blocksof a modern hybrid (applying both temporal and spatial compression viaintra-/inter-prediction) video codec is displayed in FIG. 3 .

FIG. 3 depicts a generic video codec performing both spatial andtemporal (motion) compression of a video source. The encoder blocks arecaptured within the “Encoder” tagged domain. The decoder blocks arecaptured within the “Decoder” tagged light gray domain. One skilled inthe art may associate the generic diagram from above describing a hybridcodec with a plethora of state-of-the-art video codecs, such as, but notlimited to, MPEG-1, MPEG-2, MPEG-4 (generically referred to as MPEG-x),H.264, H.265, H.266 (generically referred to as H.26x) or VP8/VP9/AV1.As such, the concepts hereby utilized shall be considered in a generalsense, unless otherwise specifically clarified and reduced in scope tosome codec embodiment hereafter.

The coded residual bitstream is then encapsulated into an elementarystream as NAL units ready for storage or transmission over a network.The NAL units are the main syntax elements of a video codec and thesemay encapsulate encoded video metadata, e.g., video/sequence/pictureparameter set (“VPS”/“SPS”/“PPS”), supplemental enhancement information(“SEI”) messages etc., and encoded video headers and residuals data,generically as picture slices (partitions of a picture, or equivalently,of a video frame). The encapsulation general syntax carries informationdescribed by codec specific semantics meant to determine the usage ofmetadata and video encoded data and aid the decoding process.

The NAL units' encapsulation syntax is composed of a header portiondetermining the beginning of a NAL unit and the type thereof, and a rawbyte payload sequence containing the NAL unit relevant information. TheNAL unit payload may subsequently be formed of a payload syntax or apayload specific header and an associated payload specific syntax. Acritical subset of NAL units is formed of parameter sets, e.g., VPS,SPS, PPS, SEI messages and configuration NAL units (also knowngenerically as non-VCL NAL units), and picture slice NAL unitscontaining video encoded data as VCL information. An effective decodermay:

-   -   implement a bitstream parser extracting the necessary metadata        information and VCL associated metadata from the NAL unit        sequence;    -   decode the VCL residual coded data sequence to its transformed        and quantized values;    -   apply the inverse linear transform and recover the residual        significant content;    -   perform intra or inter prediction to reconstruct each coding        unit luminance and chromatic representation;    -   apply additional filtering and error concealment procedures; and    -   reproduce the raw picture sequence representation as video        playback.

These operations and procedures may happen successively, as listed, orout-of-order depending on a decoder specific implementation.

Moreover, robust decoders may consider the Group of Pictures (“GoP”)structure and embedded synchronization information to implement errorconcealment mechanisms to conceal some of the visual artifacts resultedfrom potential errors in the video coded streams, either at syntacticlevel (bits), codec semantics level (video codec syntax elements) orsynchronization level (temporal sequence of frames). By definition, aGoP represents a temporal sequence of video frames starting (or ending)with an intra-coded video frame (an I-frame) followed by plurality offorward predicted frames (P-frames) or bi-directional predicted frames(B-frames). A group of pictures parameter set is further described byits associated VPS NAL unit (containing video layer attributescharacterization and encoder configuration), SPS NAL unit (containingsequence-level attributes characterization and encoder configuration),and PPS NAL unit (containing picture-level attributes characterizationand encoder configuration). A summary of main video coded frames andslices (partitions of a frame) is provided within Table 1.

TABLE 1 Frame/slice type and generic characterization with respect tointra-/inter-prediction type according to common video codecs Slice typeMeaning and content Generic importance Rate-distortion behaviorI-Frame/I-Slice May contain only High High rate, loss severely distortsintra-coded coding current picture and video coded units sequence setreferencing this slice P-Frame/P-Slice May contain only MediumLow-medium rate, loss may distort intra-coded and to some degree thecurrent picture predictive inter-coded and may affect video coded codingunits sequence set referencing this slice B-frame/B-Slice May containintra Low Low rate, loss might distort the coded and current picture andmight affect predictive/bi- video coded sequence set predictiveinter-coded referencing this slice coding units

In one embodiment, the error concealment mechanisms of state-of-the-artvideo decoders comprise two main procedures (see Zhang, F., & Bull, D.R. (2021). Intelligent image and video compression: communicatingpictures. Academic Press.): temporal copying and motion compensatedinterpolated replacement. The temporal copying approach concealscorrupted video coded blocks of a current frame/slice at playback withcopies of video coded blocks from reference frames/slices of the currentframe/slice. On the other hand, the motion compensated, and interpolatedreplacement adaptively extends the temporal copying by means of motioncompensation and intra-frame/intra-slice interpolation (via variouskernels, e.g., such as radial basis kernels (see Shahriari, A.,Fernando, W. A. C., & Arachchi, H. K. (2006, August). Adaptive errorconcealment with radial basis neuro-fuzzy networks for videocommunication over lossy channels. In First International Conference onIndustrial and Information Systems (pp. 600-604). IEEE)) utilizing themotion vectors available for the corrupted video coded blocks of acurrent frame/slice. These methods albeit simple provide effectiverule-based and consistent error concealment for video coded block visualartifacts, yet in case of high error rates of block artifacts, such asis usual the case of wireless transmissions over packet-switchednetworks, their concealment capabilities do not manage to provide highquality visual reconstructions.

Lately, advances in computer and machine vision have been utilized inthe context of image and video reconstruction. As such in the visualuncoded domain of still pictures or moving pictures (videos) deeplearning methods such as convolutional neural networks (“CNNs”), longshort-term memory (“LSTM”) models, and combinations thereof (seeSankisa, A., Punjabi, A., & Katsaggelos, A. K. (2018, October). Videoerror concealment using deep neural networks. In 2018 25th IEEEInternational Conference on Image Processing (ICIP) (pp. 380-384).IEEE.) have been used to detect and conceal errors by 2D (e.g.,horizontal, and vertical) optimal flow prediction within the uncodedpixel domain. Another approach to inpainting and blind visual recoveryof corrupted/shaded blocks/regions of video frames has been proposed(see Gao, C., Saraf, A., Huang, J. B., & Kopf, J. (2020, August).Flow-edge guided video completion. In European Conference on ComputerVision (pp. 713-729). Springer, Cham.) where again the flow and edges ofthe dynamics within the video frames have been used as discriminants toconceal errors and remove selected portions within a GoP using deeplearning fully connected models. The foregoing have achieved theseresults based on extensive training on sets of data of some similarity,e.g., similar scenery, background textures, color schemes, videodynamics.

In another embodiment, no learning from a data set may be required toperform Gaussian noise denoising, inpainting and deblurring of stillpictures (see Ulyanov, D., Vedaldi, A., & Lempitsky, V. (2018). Deepimage prior. In Proceedings of the IEEE Conference on Computer Visionand Pattern Recognition (pp. 9446-9454)). In one embodiment, this methodutilizes stochastic gradient descent to train from generic noise inputthe fully connected deep learning model of the image prior such that achosen dissimilarity metric between the corrupted picture and thereconstructed prior would be minimized. As such, the method yieldedvisually satisfying outputs and reconstructions, concealing the errorswithin the corrupted pictures by denoising, deblurring or inpaintingclose to the original pictures.

Both these trained and untrained approaches applying statisticallearning frameworks and deep learning models gain increasing tractionand their performance of satisfactory accuracy of visual recoveryapproaches the requirements of real-time applications. As such theybecome practically relevant for consideration within videocommunications applications alongside traditional receivers and videodecoders.

Regarding 3GPP RAN overview and E2E XR (Video) transport architecture,in 5G NR RAN, as well as in previous releases of 3GPP, the RAN lowerlayers have no specific knowledge of the upper layer traffic, acting asa Data Radio Bearer (“DRB”) over the physical wireless channels betweena CN/data network and a UE. As such, no optimized decision can be takenin appropriately scheduling transmissions/retransmissions of associatedtraffic and controlling the rates of various application streams withinhigh granularity and low-delay adaptability constraints of immersivemedia applications over highly mobile environments.

Interactive multimedia applications such as AR/VR/XR involving high-rateand low-latency constraints for transmission of video coded datasynchronized to some user interaction is such a specific use case with ahigh QoE requirement. To serve alike applications reliably and robustly,a RAN may benefit from metadata and actionable insights into theAR/VR/XR video traffic required to transfer over the air.

Certain embodiments, however, do not offer such capabilities andprocedures. As illustrated in FIG. 4 , the PDUs associated with an XRapplication session of an application server 402 connected to a CN 404is transferred via the CN 404 UPF over the IP to the RAN 406. Themultimedia traffic may be further supported by a real-time multimediatransport protocol such as a Real-time Transport Protocol (“RTP”) oralike to handle jitter, packet loss and out-of-order deliveries that mayoccur within a typical IP network setup.

The QoS associated with IP packets of the XR traffic is handled by theCN 404 via QoS flows 408 generated at the UPF within the established PDUsession. This procedure is opaque to the RAN 406, which only manages themapping of QoS flows 408 associated with the received IP packets totheir corresponding DRBs given the QoS profile associated with theindicators of each QoS flow 408. In a 5GS for instance the QoS flows 408will be characterized by the 5QI (see 3GPP Technical Specification TS23.501 (V17.2.0—September 2021). System architecture for the 5G System(5GS); Stage 2 (Release 17)).

This latter mapping of QoS flows 408 to DRBs is performed within the RAN406 by the Service Data Adaptation Protocol (“SDAP”) layer 410. The SDAPService Data Unit (“SDU”) is then processed by the Packet DataConvergence Protocol (“PDCP”) 412 where among others header compressionand ciphering are performed and the outputs further processed by theRadio Link Control (“RLC”) 414. The RLC 414 may perform segmentation ofthe PDCP 412 SDUs and implements the automatic request response (“ARP”)repetition retransmissions. The RLC 414 SDUs are then processed over thelogical channels interfaces by the Medium Access Control (“MAC”) layer416, which handles the logical channels multiplexing, HARQ, schedulingand scheduling retransmission functions. Lastly, the MAC PDUs arecombined over the transport channel into transport blocks (“TBs”) at thelevel of PHY layer. The PHY handles the coding/decoding, rate matching,modulation/demodulation, radio resource mapping, multiantenna mappingand other typical radio low-level functions.

The PHY TBs, which are appended with their own Cyclic Redundancy Check(“CRC”) of 16 or 24 bits blocks for detection of errors, are furtherpartitioned into same-sized coding blocks (“CBs”). The CBs are appendedas well by 24 bits CRC for error detection and following this operationthey are forward error correction (“FEC”) encoded by the PHY. The HARQprocedure within 5G NR ensures incremental redundancy retransmissions ofan entire TB in case any of the CBs or TB CRC checks fails thuseffectively ensuring reliability over the wireless link. In addition,given the increasing size of TBs, 5G NR also introduced a code blockgroup (“CBG”) construct to group one or more CBs into CBGs. The CBGs, ifconfigured appropriately via the Radio Resource Control (“RRC”), supportindependent HARQ via Downlink Control Information (“DCI”) signalingprimarily via CBG Transmit Indicator (“CBGTI”) and CBG Flush Indicator(“CBGFI”) within the same HARQ process as the enclosing TB. As such,some mechanisms for versatile retransmissions are present in 5G NR toreduce retransmissions delays and resource utilization, applicable alsoto high-rate low-latency traffic such as immersive AR/VR/XR/CGM mediaapplications. Yet these procedures are purely based on traditional FECmechanisms, and bit-exact receiver decoding, which in practice reducesthe retransmissions and associated resource utilization needs just in avery limited amount.

The RAN ensures therefore the syntactic correctness at bit level of thedata traffic over the wireless media and solves the technical problem ofthe Shannon-Weaver's general Mathematical Theory of Communication (seeShannon, C. E. (1948). A mathematical theory of communication. The Bellsystem technical journal, 27(3), 379-423.). According to the latter thegoal of communicating a message across a communications system is splitover 3 levels, the effectiveness level (concerned with “how effectivelythe received meaning affects conduct in the desired way”), the semanticlevel (concerned with “how precisely the transmitted symbols conveydesired meaning”), and the technical level (solving “how accurately thesymbols of communications be transmitted”), and moreover, the onlydesign problem of a communications system shall be limited to solvingonly the technical level. Albeit this argument is the bedrock of anycommunications system available today, latest advances advocate for theemergence of a semantic communications framework (see Strinati, E. C., &Barbarossa, S. (2021). 6G networks: Beyond Shannon towards semantic andgoal-oriented communications. Computer Networks, 190, 107930.) toleverage the ever-increasing computational capacity and autonomy ofoperation of AI and ML towards increased better communication rates,latency reduction and overall spectral efficiency of futurecommunications systems. As a result, it is of high interest to utilizethe semantic level of communications and video coded traffic awarenessto enhance the current RAN capabilities in supporting high-rate,low-latency immersive media applications without large overheads andretransmission requirements that may impact the latter's QoSrequirements.

In general, as opposed to the current art of bit-exact communications,this disclosure proposes a novel approximate semantic communicationssolution to video coded digital communications systems serving high-ratelow-delay video data streams. Thereby the bit-inexact communication ofmessage bits is allowed to the extent where the reconstruction of bitsat a receiver (post FEC decoding) following a transmission permits aprospectively noisy and distorted video reconstruction by a conventionalhybrid decoder. Within the potential noisy and distorted first videoreconstruction, the semantic video content is similarly an approximationof the original sent video content, potentially containing block noiseand edge artifacts as a by-product of video decoding with potentiallynot bit-exact video coded data.

The visual artifacts, in one embodiment, are specific to the videodecoder inner error concealment procedures as previously detailed. Tocorrect for the latter and provide a genuine, high-quality,low-distorted reconstruction and convene the semantic meaning of thetransmitted video coded message additional error correction over thevideo uncoded domain is performed. The latter step is defined as a videosemantic error correction processing block wherein the intrinsicspatial-temporal joint distribution of the pixels within the videoframes to be semantically reconstructed and corrected, and of the pixelsin adjacent and referenced video frames is utilized to minimize aquantitative distortion metric (e.g., a minimum squared error (“MSE”), ap-norm, an entropy-based function etc.). As such, this intrinsic jointdistribution acts as the prior information and is utilized by means ofmachine vision algorithms and trained or non-trained (wherein trainingis referred to the act of supervised optimization of a neural network'scomponents based on a training set forming a common category with theobject inputs) neural networks to obtain a semantic error-correctedversion of the original image. The post-processing shall thus aid incorrecting artifacts (e.g., by means of denoising, prior-driveninpainting applied either at block, sub-picture or picture level), suchas block Gaussian noise, block correlated noise, edge noise and decodingartifacts that hybrid video decoder error concealment could not resolvealone.

This two-step video error concealment determines a smart video decoder,which can be leveraged by novel video coded communications systems bymeans of the approximate semantic communications model brieflyintroduced and described above, and further outlined in FIG. 5 . At thevideo semantic level applicable to the framework of semanticcommunications (see Shannon, C. E. (1948). A mathematical theory ofcommunication. The Bell system technical journal, 27(3), 379-423.;Strinati, E. C., & Barbarossa, S. (2021). 6G networks: Beyond Shannontowards semantic and goal-oriented communications. Computer Networks,190, 107930.) hereafter the proposed solution set contains of aknowledge base 502, a video semantic encoder 504 and a video semanticdecoder 508.

The knowledge base 502 determining the semantic encoding/decodingprocedures of the video semantic information to video messages isrepresented by a video codec specification used to encode a raw uncodedvideo source. This is a consequence of the operation methodology ofmodern hybrid video codecs where semantics are inherently consideredwithin the encoding process given the recursive block partitioning ofpictures and the spatial-temporal prediction models. Albeit notontologically labelled, the latter video semantic elements, andstructures thereof, are embedded into the compression/decompressionprocedures and extending the prior knowledge embedded semanticallywithin a specific group of video frames up for semantic errorcorrection. An example of knowledge base embodiments is the H.26x familyof Motion Pictures Experts Group (MPEG) video codecs (e.g., H.264,H.265, H.266).

The video semantic encoder 504 is therefore represented by an associatedvideo codec encoder given the video codec knowledge base realization.Whereas the video semantic decoder 508 is a smart video decoder, asdefined above, wherein the first video decoder processing component isrepresented by an associated video codec decoder 506 given the videocodec knowledge base realization, and the second semantic errorcorrection block 510 is possibly jointly optimized with the video codecknowledge base and/or corresponding first video decoder processingcomponent.

As seen in the bottom side of FIG. 5 , a communication system 512 ispresented that is applicable to video coded traffic of immersive,high-rate and low-latency applications such as AR/VR/XR/CGM thatembodies the approximate semantic communications methodology herebybriefly described that differentiates from conventional methods ofbit-exact communication systems in allowing certain level of bit-errorspost-FEC channel decoding and applying the necessary level of correctionand reconstruction at a semantic level instead. The methodology of suchapproaches, in one embodiment, pays prospective dividends in reducedHARQ process load, reduced retransmission needs, dynamic modulation andcoding scheme (“MCS”) for rate adaption, and general optimization ofradio resource utilization. To this extent, following high-level steps(that may be broken down into multiple lower-level steps and associatedsignaling as detailed in the following embodiments) are necessary:

-   -   an indication to a transmitter of a receiver's capabilities for        semantic error correction;    -   a transmission from a transmitter to a receiver of video coded        stream comprising of approximate semantic communications,        wherein the receiver applies a smart video decoder with embedded        semantic error correction to reconstruct the sent video semantic        content    -   an enhanced signaling indication of HARQ acknowledgement        feedback in support of the approximate semantic communications        of bit-inexact data post-FEC channel decoding.

In one embodiment, shown in FIG. 6 , which depicts a smart video decoderwith embedded functionality for semantic error correction in support ofvideo approximate semantic communications where the top is a realizationof a smart video decoder with separate video source decoding andsemantic error correction steps and the bottom is a realization of asmart video decoder as a singular joint video source decoding andsemantic error correction model, a smart video decoder 602 at areceiver, as defined, consists of the capabilities to decode a videocoded stream and to apply successive semantic error correction on thedecoded video content to conceal any visual artifacts as by-product ofbit-wise errors within a received video coded stream considered asinput. In one embodiment, the required processing of a smart videodecoder may be split between two processing blocks, a first hybrid videodecoder 604 implementation and a second semantic error correction block606 for advanced visual error concealment, wherein the block may consistof an in-video prior knowledge module 608, which may be a learned modeland/or a non-learned prior-driven model for semantic inference and errorcorrection for the advanced video error concealment. The latterprocessing block's sub-components may be optimized given the knowledgebase semantics of the video codec specification. In such examples, thesecond processing block of a smart video decoder 604 may be bypassed interms of active processing for purposes of semantic error correctionwhen the video coded input stream is received without syntactic errors,e.g., bit-exact, as its originally sent counterpart.

On the other hand, in some embodiments, the smart video decoder 602 maybe a singular video neural decoder model 610, jointly optimized tofulfill the defined functionality of the smart video decoder, e.g., toperform joint video codec decoding and semantic error correction foradvanced visual error concealment. In such examples, the knowledge basesemantics 612 (e.g., the video codec specification semantics) of thevideo codec syntax elements are applied to conceal video error locationswithin detected erroneous blocks of bits (detected for instance by meansof PHY FEC decoding-based signaling) in the video coded bitstream andthus semantically correct errors within the NAL units' headers andpayloads. The semantic error correction of such an embodiment of thesmart video decoder is therefore inherently and jointly optimized basedon cached (e.g., a video codec specification) and/or prior (e.g., one ormore previously decoded/concealed video frames) knowledge baseinformation as part of one neural model 610. A schematic of suchrealizations of the defined smart video decoder is provided in thebottom side of FIG. 6 .

As the smart video decoder 602 as a receiver provides the set offunctions necessary to support the semantic reconstruction of the videocontent beyond bit-exact inputs, knowledge of the capabilities andextent of tolerated errors is detrimental for a transmitter to optimizevideo transmissions/retransmissions and associated radio resourceallocations. The capabilities of the receiver in terms of a smart videodecoder are therefore of interest to be indicated for a RANimplementation. Therefore, from a RAN perspective a supported UEcapabilities undergoing video approximate semantic communications may beleveraged in controlling the HARQ retransmission process, feedback outerloop adaption, scheduling decision given a tight PDB QoS flows budget,energy efficiency optimization by optimized (discontinuous reception)DRX configuration of UEs or optimization of the mobility management forimmersive and interactive media applications such as AR/VR/XR/CGM.

In one embodiment, the capabilities of a UE with a smart video decoder602 supporting video approximate semantic communications to be reportedcomprise of at least one of:

-   -   an enablement flag as a one-bit indicator (e.g., SEC_ON,        SEC_OFF) representing that the video semantic error correction        necessary for the video approximate semantic communications is        enabled or disabled;    -   a maximum error rate threshold that the semantic error        correction functionality of the video approximate semantic        communications mode can tolerate and semantically correct video        errors for in order to achieve a fixed video average        reconstruction quality given a fixed quality indicator criterion        (e.g., minimum MSE (“MMSE”), Peak Signal-to-Noise Ratio        (“PSNR”), structural similarity index (“SSIM”), video        multi-method assessment function (“VMAF”) or equivalent        metrics);    -   a statistical running window configuration over which the error        rate statistic is monitored (e.g., aggregated) and compared with        the maximum error rate threshold of the semantic error        correction functionality in semantically correcting video errors        to achieve a fixed video average reconstruction quality, whereas        the statistical running window configuration is determined by at        least a type of error unit monitored post FEC decoding (e.g.,        PHY block error rate (“BLER”) at a CBG/TB level, aggregated        log-likelihood ratio (“LLR”) at a CB, CBG or TB level and/or        alike PHY transport units error statistic describing the binary        decision making between an erroneous PHY transmission and a        non-erroneous PHY transmission) and a length thereof;    -   a maximum processing delay, wherein the maximum processing delay        can be further split into a video decoding processing delay and        a video semantic error correction processing delay;    -   an average energy consumption indicator estimation, wherein the        estimate of average energy consumed may comprise of a first        component estimate of average energy consumed with the semantic        error correction enabled and a second component estimate of        average energy consumed with the semantic error correction        disabled;    -   a power source indicator as a one-bit indicator determining the        type of power used (e.g., a ‘0’ indication for ON_BATTERY and a        ‘1’ indication for ON_AC, e.g., powered by AC current source);    -   an indication determining the maximum video frame mobility and        change rate (e.g., no-mobility video frames, i.e., still scene        without change, low-mobility video frames, medium-mobility video        frames, or high-mobility video frames), that the semantic error        correction functionality can tolerate and process to achieve        successfully a fixed video reconstruction quality; and    -   a standalone operation flag as a one-bit indicator describing        whether the UE requires assistance from the RAN, more        specifically from a gNB, to monitor the transmission errors        within a configured statistical running window and to        enable/disable accordingly given its own capabilities the        semantic error correction, or alternatively, that the UE handles        all these steps in a standalone manner, i.e., not assisted.

In some embodiments the semantic error threshold is indicated as acoding BLER determined based on the reported number of CBGs/TBs errors.In one embodiment this metric is monitored across a window of one ormore encapsulating TBs. In another embodiment, the statistical runningwindow over which this metric is monitored may be configured to thelevel of CBGs or any dynamic segmentation of at least one TB.

In other embodiments, the semantic error threshold is indicated as anLLR determined based on LLR indicators corresponding to individual CBs.In one embodiment these individual LLRs can be further aggregated toprovide a common LLR indicator across a window of one or moreencapsulating TBs. In another embodiment, the statistical running windowacross which a common LLR indicator statistic can be further aggregatedis configured to the level of CBGs or any dynamic segmentation of atleast one TB. In some examples, the weights associated with the commonaggregated LLR indicator statistic over the running window may beunequally determined by an implementation specific criterion (e.g., sizeof the associated CBs, importance indicator of the associated CBs forXR/video traffic importance-aware transmissions, and/or the like).

In a video coded traffic-aware embodiment, (wherein the awareness isdefined as knowledge of the lower-level RAN, e.g., MAC/PHY, of NALunits' boundaries and/or importance thereof, and/or type of videoframes, such as I-frame/P-frame, or the like), the semantic errorthreshold is indicated based on NAL units' error rate (“NALuER”). Insuch an example this metric is monitored across one or more TBscontaining the identified NAL units. In some embodiments, NAL units orsegments thereof, required for synchronization of decoding operationsand error concealment tasks, e.g., access unit delimiter, NAL VPS, NALSPS, NAL PPS, are to be transmitted bit-exact and for this purpose theencapsulating PHY transport elements, e.g., TBs/CBGs, are undergoingcurrent art HARQ process procedures requiring retransmissions pendingnon-acknowledgement (“NACK”) signaling from the receiver for post FECerroneous decoding.

The UE capabilities to support video approximate semantic communicationsare reported, in one embodiment, semi-statically by means of a bit fieldwithin the RRC signaling over a Physical Uplink Control Channel(“PUCCH”). In some embodiments such capabilities to support videoapproximate semantic communications are updated via a bit field withinat least one of an Uplink Control Information (“UCI”) signaling, a UCIscheduling request over the PUCCH for the Physical Uplink Shared Channel(“PUSCH”), and/or the like.

In some embodiments, the transient video semantic error correctionenablement is configured dynamically by a gNB over one of a DCI bitfield over the Physical Downlink Control Channel (“PDCCH”), a DCIsignaling over the Physical Downlink Shared Channel (“PDSCH”) or a MACControl Element (“MAC-CE”) signal, such that the enablement flag is setto SEC_ON to enable approximate video semantic communications with asupporting UE, or respectively, is set to SEC_OFF to disable approximatevideo semantic communications with a UE. In other embodiments, the UEmay indicate to the gNB its readiness/willingness to switch toapproximate video semantic communications mode by setting the enablementbit to SEC_ON within one of a UCI scheduling request over a PUCCH and abit field MAC-CE signaling. However, in such embodiments the gNB decidesfinally whether the request for SEC_ON from the UE is accepted bysignaling over to the UE the final state of the enablement bit in one ofa following DCI bit field or a MAC-CE signaling. On the other hand, inother embodiments, the UE may indicate to the gNB its transient lack ofsupport for approximate video semantic communications mode by settingthe enablement bit of semantic error correction to SEC_OFF within one ofa UCI bit field signaling over PUCCH, a UCI signaling for a datacommunication over the PUSCH or a bit field MAC-CE signaling.

In some embodiments, the UE driven requests for enabling/disabling thevideo approximate semantic communications mode may be subsequentlysupplemented by one of a UCI bit field or a MAC-CE bit field containinga reason for the request. In one example, such a bit field comprises aone-bit field corresponding to an indicator for the associated UE powersource state. As such, two-bits tuple requests of (SEC_ON, ON_AC) or(SEC_OFF, ON_BATTERY) may be received by a gNB to justify the UE invokedswitch of semantic error correction and implicit the support for videoapproximate semantic communications mode.

Depending on the video coded traffic direction of an immersive mediaapplication, the solution space of a video approximate semanticcommunications systems, as defined in the prequel, is separated into twocategories. These are namely the one representing the DL direction(where a gNB within a RAN serves with video coded traffic a UE whoseconfiguration may enable the video approximate semantic communicationsmode), or on the other hand, the UP direction (where a video mediacapturing UE transmits video coded traffic data to a gNB within aconnected RAN, whereby the RAN/gNB or a video coded traffic dataendpoint have the capability and afferent delay budget of videoapproximate semantic communications via semantic error correction).

Treating the DL communications direction, in one embodiment, where theUE has embedded support for the video approximate semanticcommunications mode and this is enabled by one of the procedurespreviously described, the RAN may assist the UE and take decisionswhether to retransmit erroneously transmitted information by means ofthe HARQ process associated with a TB served to the UE. The latterdecision is based on the HARQ feedback reported by the UE and itsgranularity (e.g., per TB or CBG, given that the CBG HARQ retransmissionconfiguration has been appropriately configured conform (see 5.1.7.2 of3GPP Technical Specification TS 38.214 (v16.5.0—April 2021). 5G; NR;Physical layer procedures for data) via the CBGTI over DCI signaling,respectively). As such RAN-assistance for UEs in video approximatesemantic communications is provided for some UEs of reducedimplementation complexity.

As such, in some embodiments, the decisions to retransmit CBGs and/orTBs are made solely by the RAN given the feedback received at a gNB fromthe UE, and the knowledge the RAN has of the respective UE videosemantic error correction capabilities and enablement status. The UEtransmits therefore the regular HARQ feedback associated with currentart 5G NR based on the CRC checks performed on a per CB/per TB basis,and consequently, given the RAN available configuration of the videoapproximate semantic communications mode of the UE, the RAN determineswhether any retransmission is necessary.

FIG. 7 depicts one embodiment of RAN level support for monitoring ofHARQ processes and retransmissions for gNB-assisted video approximatesemantic communications in DL. Example considers an error rate thresholdof 0.4 for semantic error correction and a statistical running window of3 transport units (e.g., CBGs/TBs). Three examples are presented: (1) noerrors are encountered—regular operation, (2) errors do not exceedconfigured error rate threshold—no retransmissions needed as semanticerror correction applied, (3) errors do exceed configured error ratethreshold—retransmissions needed to apply semantic error correction.

In one example, as presented in FIG. 7 (1) 702, if all the CBGs/TBs 706within a running window 704 for statistical aggregation are ACKed 708,the RAN proceeds regularly with scheduling for transmission of upcomingfresh transmissions as no data has been corrupted. In another example,presented in FIG. 7 , if some CBGs/TBs 706 within a running window forstatistics aggregation on the RAN side are NACKed 710, and the restACKed 708, the RAN computes the statistics according to the type ofthreshold supported by the UE (e.g., in terms of BLER, in terms ofaggregated LLR indicator or in terms of NALuER). Given the latterstatistics determination at the RAN over the configured monitoringrunning window, the RAN compares the statistical result with thesemantic error correction threshold achievable by the associated UE.

In some examples, as portrayed in FIG. 7 (2) 712, if the RAN computedstatistical result is lower than the UE semantic error correctionthreshold indicator, the RAN decides not to subsequently retransmit anyCBGs/TBs 706 and UE is responsible to apply semantic error correction tothe bit-corrupted video frames to conceal the existing error artifactsremaining post-decoding. As the semantic meaning posterior to semanticerror correction at the video frame/picture/sub-picture level isreconstructed approximately close to the originally transmitted videoinformation within the reported semantic error correction threshold, nofurther retransmissions of the corrupted data are necessary. The UE isresponsible thus to recover the semantic video meaning of the originallysent messages. This operation may be performed autonomously by the UE insome embodiments, whereas in other embodiments an explicit indication bythe gNB may be signaled via at least one of a Demodulation ReferenceSignal (“DM-RS”) embedded signaling part of the originally transmittedTBs 706 over the PDSCH, and a dedicated DCI bit field signaling over thePDCCH.

In other examples, as shown in FIG. 7 (3) 714, if the RAN computedstatistical result is greater or equal to the UE semantic errorcorrection threshold indicator, the RAN decides to retransmit aplurality of CBs as one or more CBGs/TBs 706 (upon a determined videoapproximate semantic communications statistical window configuration andHARQ configuration), covering the corrupted CBGs/TBs such that eitherthe statistical error at least decreases below the semantic errorcorrection threshold or, equivalently, all the errors are corrected bythe retransmissions. In some examples therefore, segments of TBs 706 maybe retransmitted by a gNB individually as CBGs given prior enablement ofthe CBGTI flag within the DCI scheduling prior to the said TBstransmission, e.g., according to the procedures of 5.1.7.2 of 3GPPTechnical Specification TS 38.214 (v16.5.0—April 2021). 5G; NR; Physicallayer procedures for data.

In some embodiments, to support the UE semantic error threshold type(e.g., BLER, LLR, NALuER indication, or the like), the RAN performs theoperations of mapping the HARQ feedback reported by the UE to therespective semantic error correction threshold measure type. To acquirethe necessary granularity to perform such calculations, the RAN may needadditional HARQ feedback information from the UE. In one example, wherethe semantic error correction threshold of the UE is determined based onthe BLER, the gNB may therefore simply enable CBG HARQ feedback withmultiple bits (one bit per each CBG within a TB) via CBGTI, e.g.,according to 5.1.7.2 of 3GPP Technical Specification TS 38.214(v16.5.0—April 2021). 5G; NR; Physical layer procedures for data.

On the other hand, in other embodiments, each unit of the UE HARQfeedback report may contain a multiple bit depth description of thechannel decoding procedure outcome (ACK/NACK) as a soft component. Tothis extent, a floating-point representation normalized to the interval0 to 1, where 0 quantifies a completely uncertain event and 1 quantifiesa completely certain event, or equivalently an indexed/quantizedspecification thereof, may quantifies in some examples the ACK/NACKreports and their confidence, as a tuple of the form (ACK/NACK, ACK/NACKstatistical confidence), as (HARQ feedback bit, HARQ feedback confidencebits), wherein the latter part is directly linked to the CBs aggregatedLLR across a unit of HARQ feedback (e.g., CBGs/TBs). In some examples,these confidence levels may be split by quantization into two stages,e.g., LOW_CONF, HIGH_CONF for a 2-bit wide representation of allpossible tuples, whereas in some other examples a finer level ofgranularity may be utilized, e.g., LOW_CONF, MEDIUM_CONF, HIGH_CONF forup to a 3-bit wide representation of all possible HARQ feedback tuples.

In addition, in some embodiments for which the semantic error thresholdof a UE is expressed based on an LLR or a NALuER indication, the HARQfeedback is further extended to multibit feedback per each CB to allowthe gNB to better track the required statistics required for thedecision making at either an LLR or a NALuER (in case of video codedtraffic-aware embodiments) level. For a compacted representation, thetuple may be mapped to a bitfield representation based on anindexed/tabulated representation of quantized confidence intervals. Thisextended HARQ signaling from the UE to the gNB shall be reported over tothe PUCCH via HARQ dedicated UCI resources. Furthermore, theconfiguration of CB-wise reporting may be signaled by appropriateconfiguration of a number of CBGs to the number of CBs in the TB, e.g.,conform to 5.1.7.1 of 3GPP Technical Specification TS 38.214(v16.5.0—April 2021). 5G; NR; Physical layer procedures for data,signaled via the CBGTI within the DCI scheduling request over PDSCH.

As the energy consumption of a semantic error correction block may besignificant for battery-powered immersive media playback devices, e.g.,AR/VR glasses, 3D light field displays, and/or the like, in oneembodiment, the UE can report to the gNB additional status indicationsof its energy levels which may influence its capabilities to performsemantic error correction and to operate within the video approximatesemantic communications mode. As such, in some embodiments, the UE mayindicate to the gNB transient semantic error correction capabilities pervideo coded stream bases whereby the ACK/NACK report for a stream servedover a DRB is extended to include the setup of the semantic errorcorrection enablement flag and a battery 1-bit indicator.

In one example where the semantic error correction enablement bit isset, e.g., SEC_ON, a battery indicator BATT CRIT, e.g., set to ‘1’,indicates that the UE battery level has dropped under a threshold wheremultiple video coded stream support for video approximate semanticcommunications is disabled and only one stream/DRB process can undergosemantic error correction. Alternatively, if BATT_OK, e.g., set to ‘0’,normal operation of semantic error correction within the domain of theUE smart video decoder is possible given the enablement flagconfiguration, e.g., enabled as SEC_ON, or disabled as SEC_OFF. Lastly,in some embodiments where the semantic error correction enablement flagis SEC_OFF and the battery indicator is BATT CRIT, the UE signalstherefore to the gNB that the semantic error correction is not possiblefor any video coded stream DRB given the current battery status whichdropped below a minimum supported threshold. The associated indicationof joint semantic error correction enablement flag and battery statusindicator, summarized in Table 2, may be signaled by at least one of aUCI bit field indication as part of a grant scheduling request, a UCIbit field indication as part of a HARQ feedback enhanced informationtuple, and a MAC-CE indication for semi-static update of the UEcapabilities.

TABLE 2 Collection of video semantic error correction and battery statuscapabilities and associated signaling for energy-aware video approximatesemantic communications Semantic error Battery correction statusenablement indicator Case flag flag Associated signaling meaning 0SEC_ON BATT_OK Normal UE operation with enabled video semantic errorcorrection 1 SEC_ON BATT_CRIT Reduced UE operation of enabled videosemantic error correction for only one video coded stream 2 SEC_OFFBATT_OK Disabled semantic error correction with UE battery supportingnormal semantic error correction operation 3 SEC_OFF BATT_CRIT Disabledsemantic error correction with UE battery supporting reduced operationof semantic error correction for only one video coded stream.

Based on the signaling described in Table 2, energy-awareness of a UEsupporting video approximate semantic communications is provided to thegNB and to its corresponding RAN, which subsequently may utilize theembedded information for optimization of energy-efficient low-level RANscheduling, procedures and protocols pertaining to video coded trafficof immersive, high-rate, low-latency advanced AR/VR/XR/CGM applications.

In some embodiments, a RAN implementation may further support UE-sideerror concealment of video coded traffic by predictive caching ofon-demand keyframe (e.g., I-frame/I-slices video coded data) at the gNBside or by predictive filtering of enhancement layers to meet set QoSflows requirements of PER and PDB and consequently lower the frame/sliceerror rate of the video coded data traffic.

As such, in one embodiment, a delay-aware scheduler monitors anddetermines dynamically the probability of reaching a QoS flow fixed PER,e.g., ∈_(PER), (determining a desired over-the-air transmission videoframe/slice error rate) within a latency time constraint τ lower thanthe QoS flow PDB given the wireless link and traffic availablestatistics at a gNB. Consequently, the conditional probability measureP(τ≤PDB|∈_(PER)=PER) is estimated. Based on this estimate, the RAN maydetect a violation of the (PDB, PER) conditions set and on-demandrequest from the application server a concealment (keyframe) video codedframe/slice as an I-frame/I-slice to be transmitted to UE and stop videoerror propagation, thus concealing the latter. The on-demand requestedkeyframe is then cached within the RAN for transmission by a gNB insupport of video error concealment to a UE with or without support of anenabled semantic error correction as previously detailed. The latterprocedure is applicable provided that the on-demand keyframe requestservice time is small enough and does not violate therefore with highprobability the PDB constraint of the associated QoS flow of the videocoded traffic.

In another embodiment, whereby multi-layered video coded data traffic isbeing transported over a RAN to a UE, the same conditional probabilitymeasure P(τ≤PDB|∈_(PER)=PER) is used by a video coded traffic-awareimplementation to determine whether the transmission of themulti-layered video coded data traffic violates the QoS flowconstraints. In such an example the latency (τ) and error rate (∈_(PER))are affinely weighted combinations of the expected associated videocoded layers latencies and error rates (given the wireless linkstatistics and selected MCS), respectively, whereby the affine weightingcoefficients are determined based on the data rates associated with eachvideo coded layer, e.g.,

$\begin{matrix}{\tau\overset{\bigtriangleup}{=}{\sum\limits_{0 \leq i < {L - 1}}{w_{i}\tau_{i}}}} & {{Eq}.1}\end{matrix}$ $\begin{matrix}{\epsilon_{PER}\overset{\bigtriangleup}{=}{\sum\limits_{0 \leq i < {L - 1}}{w_{i}\epsilon_{{PER},i}}}} & {{Eq}.2}\end{matrix}$

wherein the base layer is denoted by index 0 and enhancement layers aredenoted by non-zero indices. In one example, the weights w_(i) aredetermined by the ratio between the data rate of the video coded databelonging to the i-th video layer and the sum data rate of the pluralityof video coded layers forming the video coded stream data. In suchembodiments, the RAN may further assist a UE with or without enabledsupport of semantic error correction with the error concealment bydynamic out filtering of layers (e.g., upper enhancement layers), thusadaptively and temporarily reducing the video rendering quality, yetavoiding higher PER and subsequent playback buffering and visual blockartifacts effects.

In other embodiments, whereby UEs do not require RAN assistance forenablement of video approximate semantic communications, a UE maysinglehandedly monitor its received CBs/CBGs/TBs status across apredetermined statistical running window and map the latter statisticsto a decision of whether or not subsequent retransmission of CBGs/TBs isrequired from the gNB. The latter UE mapping is based on a decisioncomparing the speculative error statistic determined post channeldecoding at a level of BLER/LLR/NALuER and the knowledge of the semanticerror correction capabilities of a smart video decoder at said UE.

As such, in some embodiments, a UE may control its own inner processingloop up to implementation specifics, simply signaling ACK/NACK HARQfeedback indications over UCI signaling, such that the video approximatesemantic communications mode is supported transparently to any RANinstantiation. However, in most of the operating cases RAN awareness ofthe operations performed by a UE where RAN support may be needed (e.g.,retransmissions of part or complete TBs, dynamic adaptation ofretransmissions delay loop, dynamic adaption to wireless link fading ofMCS etc.), and as such additional enhanced signaling from UE regardingthe processing by semantic error correction in the video approximatesemantic communications mode is desirable.

In addition to the semi-static UE capabilities information indicationsearlier described, in some embodiments, a dynamic signaling of the UEincurred post channel decoding processing within a unit of HARQ feedbackcan be signaled to inform the gNB on one hand of the CBs/CBGs/TBsreceived status, and on the other hand, to indicate supplementalinformation regarding at least one of a soft quality indicator of thelatter transport blocks processing and ACK/NACK decision at the UEreceiver, and an indicator of the application of semantic errorcorrection to correct remaining errors post channel decoding forconcealment of visual artifacts.

In a reduced signaling embodiment, two bits are to be utilized withinthe HARQ feedback indication to cover the PDSCH decoding decision, e.g.,ACK/NACK, and respectively the video approximate semantic communicationsdecision at the UE given its capabilities for semantic error correction.As such, a first bit per unit of HARQ feedback (e.g., CBs/CBGs/TBs) isreserved for ACK/NACK indication, whereas a second bit per unit of HARQfeedback (e.g., CBs/CBGs/TBs) is reserved for additional informationpertaining to the joint PDSCH decoding and application of semantic errorcorrection determining the necessity of subsequent retransmissions for aTB or a segment thereof. For instance, in an embodiment, the second bitmay be set depending on the value of the first bit as follows.

For a NACK indication of PDSCH decoding a second bit of ‘0’ indicates aNACK that requires retransmission, e.g., even with SEC_ON the UE cannotvisually recover the transmitted video coded data. On the other hand,for a NACK indication of PDSCH decoding a second bit of ‘1’ indicates aNACK that does not require retransmission upon the enablement of thevideo approximate semantic communications mode as the UE determined thatits capabilities of semantic error correction satisfy the empiricalstatistics collected to resolve the visual artifacts of the erroneousvideo data. However, for a disabled video approximate semanticcommunications mode a second bit indication of ‘1’ indicates a NACKgiven PDSCH decoding whereas the confidence of the decision was low,e.g., the PDSCH decoding procedure implementation of the UE could notcorrect a TB or segment thereof under low confidence, given any softdecoding algorithm involved (e.g., LDPC LLR decoding).

For an ACK indication of PDSCH decoding a second bit of ‘0’ indicatesthat the PDSCH decoding has passed albeit the confidence of the passdecision at UE receiver side was low, given any soft decoding algorithminvolved for the channel FEC decoding (e.g., LDPC LLR decoding).Oppositely, a second bit of ‘1’ indicates that the PDSCH decoding haspassed and the confidence of the pass decision at the UE receiver sidewas high. This type of soft information associated with the ACK HARQfeedback is therefore a consequence of a UE mapping of its PDSCHdecoding ability given the instantaneous wireless channel and thereforewithin an implementation can be directly mapped to a dynamic indicationof channel quality relative to the UE decoding ability, MCS and radioresource allocation selection.

As such, this information further aids as well the gNB inner loop andouter loop adaptation to meeting low BLER (e.g., within [10⁻⁴, 10⁻⁹)) infast fading wireless channels as soft information signaling within HARQfeedback may be necessary within 3GPP 5G NR for fast and dynamicadaption meeting ultra-reliable low-latency communications (“URLLC”)requirements, e.g., see R1-2101460, CSI enhancement for IOT and URLLC,submitted by QUALCOMM to RAN1 Meeting #104-e Jan. 25-Feb. 5, 2021; andR1-2100269, CSI Feedback Enhancements for IIoT/URLLC, submitted byERICSSON to RAN1 Meeting #104-e Jan. 25-Feb. 5, 2021. Concretely, in anexample, an ACK with LOW_CONFIDENCE, or a NACK with SEC_ON may trigger areconfiguration of the MCS adaption at the gNB and/or increase theback-off retransmission timer in some implementations. As such, alsogiven the fact that immersive AR/VR/XR applications may be categorizedas mixed enhanced mobile broadband (“eMBB”) and URLLC traffic, by theproposed signal both the novel video approximate semantic communicationsmode and the legacy bit-exact communications mode are simultaneouslysupported and/or enhanced. The 2-bit indication is summarized withinTable 3 for both communication modes, e.g., legacy bit-exact and theproposed video approximate semantic communications.

TABLE 3 Example of a 2-bit realization encoding of a HARQ ACK-NACKfeedback with soft information and support of video approximate semanticcommunications. Syntactic Syntactic Disabled video approximate Enabledvideo approximate first bit second bit semantic communication semanticcommunication encoding encoding encoding encoding 0 0 (NACK, HIGH_CONF)(NACK, HIGH_CONF) NACK signaled with high NACK signaled with highconfidence; very low SNR confidence; very low SNR given given configuredMCS configured MCS 0 1 (NACK, LOW_CONF) (NACK, SEC_ON) NACK signaledwith low An ACK by means of enabled confidence; potential transientsemantic error correction - no deep fade due to low SNR need toretransmit given configured MCS 1 0 (ACK, LOW_CONF) (ACK, LOW_CONF) ACKsignaled with low ACK signaled with low confidence confidence 1 1 (ACK,HIGH_CONF) (ACK, HIGH_CONF) ACK signaled with high ACK signaled withhigh confidence confidence

Extensions of the previous 2-bit signaling embodiment to multiple bitsoft information width can easily be performed by one skilled in the artby abstractly following the description provided within the previousembodiments. To this extent, multiple bits (rather than one bit alonewithin the 2-bit discussed signaling) are reserved to provide finergranularity to the soft information accompanying the ACK/NACK HARQindication. An example of this is portrayed in Table 4 for a 3-bitsignaling scheme.

TABLE 4 Example of a 3-bit realization encoding of a HARQ ACK-NACKfeedback with soft information and support of video approximate semanticcommunications. Syntactic Syntactic Syntactic Disabled video approximateEnabled video approximate 1st bit 2nd bit 3rd bit semantic communicationsemantic communication encoding encoding encoding encoding encoding 0 00 (NACK, HIGH_CONF) (NACK, HIGH_CONF) NACK signaled with high NACKsignaled with high confidence; confidence; 0 0 1 (NACK, MED_HIGH_CONF)(NACK, NACK signaled with medium MED_HIGH_CONF) high confidence; NACKsignaled with medium high confidence; 0 1 0 (NACK, MED_LOW_CONF) (NACK,MED_LOW_CONF) NACK signaled with medium NACK signaled with medium lowconfidence; low confidence; 0 1 1 (NACK, LOW_CONF) (NACK, SEC_ON) NACKsignaled with low An ACK by means of enabled confidence; semantic errorcorrection - no need to retransmit 1 0 0 (ACK, LOW_CONF) (ACK, LOW_CONF)ACK signaled with low ACK signaled with low confidence; confidence; 1 01 (ACK, MED_LOW_CONF) (ACK, MED_LOW_CONF) ACK signaled with medium ACKsignaled with medium low confidence; low confidence; 1 1 0 (ACK,MED_HIGH_CONF) (ACK, MED_HIGH_CONF) ACK signaled with medium ACKsignaled with medium high confidence; high confidence; 1 1 1 (ACK,HIGH_CONF) (ACK, HIGH_CONF) ACK signaled with high ACK signaled withhigh confidence; confidence;

In an example, a UE provides a set of HARQ-ACK with soft information ina first HARQ-ACK codebook, and a set of HARQ-ACK without softinformation in a second HARQ-ACK codebook.

In another example, a timer starts after receiving an indication (eitherfrom UE or from gNB) of enabling semantic error correction and videoapproximate semantic communications mode for DL transmissions, and theUE starts transmitting HARQ-ACK with soft information until the timerexpires or another indication of enabling/extending the semantic errorcorrection and video approximate semantic communications mode for DLtransmissions is received. The UE stops transmitting HARQ-ACK with softinformation when the timer expires.

In an example, a UE receives an indication from the gNB indicating toenable semantic error correction and video approximate semanticcommunications mode for DL transmissions. In such an embodiment, the UEtransmits HARQ-ACKs with soft information in response to DL transmissionuntil the UE receives another indication to disable semantic errorcorrection and video approximate semantic communications mode for DLtransmissions. The UE may then transmit HARQ-ACK without softinformation. The indication(s) can be provided to the UE via DCIscheduling DL transmissions.

In an example, the enabling/disabling semantic error correction andvideo approximate semantic communications mode for DL transmissions maybe performed certain time after receiving an indication indicating theenabling/disabling. The UE provides HARQ-ACK with soft information afterthe application delay is elapsed from the time the enabling/disablingindication is received.

In one embodiment, a RAN implementation with support for videoapproximate semantic communications and semantic error correction maydynamically apply the latter to aid the UL video coded datacommunications with immersive, high-rate, low-latency characteristicsspecific to AR/XR/VR or advanced CGM applications. To this degree, a RANimplementation may support a UL realization of the video approximatesemantic communications mode whereby at least the high-level proceduresbelow are required in case errors are present post PUSCH FEC decoding:

-   -   Determine whether delay budget allows for semantic error        correction given the QoS flow associated with the DRB of the UL        video coded traffic PDB requirements and knowledge of RAN        processing delay, instantaneous RAN load, and/or CN expected        delay;    -   If delay budget allows to perform semantic error correction        necessary steps for UL transmissions (e.g., at least video        decoding, semantic error correction, and re-encoding with same        video codec under the same input video codec configuration or a        low-delay configuration variant thereof);    -   Configure the UE retransmission resources and grants accordingly        to semantic error correction dynamic capabilities; and    -   Transmit further over the RAN upper layers the potentially        semantic error corrected video coded data to the CN.

The procedure described in the above embodiment may require additionalsignaling to the UE for synchronization between the operations performedat the RAN and the expected communications feedback at the UE. Thus, insome embodiments, even though the steps detailed above are dependent ona RAN specific implementation in support of video approximate semanticcommunications, the associated system-level signaling mechanism, e.g.,HARQ feedback and/or configuration of UE retransmissions resources, mayrequire extension and enhanced signaling to support subject matterdisclosed herein.

In embodiments where no errors post PUSCH decoding are encountered, orin embodiments where errors post PUSCH decoding are detected and the RANdoes not have the necessary resources to satisfy the QoS flow orsemantic error correction processing required constraints (e.g., notenough delay budget available for required processing, RAN load exceedscertain processing threshold etc.), the RAN signaling and associatedprocedures with respect to the UE UL traffic remain unchanged. As such,as in the UL HARQ feedback in 5G NR is asynchronous and implicit basedon the DCI scheduling grants of UL traffic, for retransmissions DCIscheduling of UL PUSCH traffic configured with the HARQ process numberof the original transmission and no new data indication (configured viathe new data indicator (“NDI”) bitfield) is utilized as an implicitHARQ-NACK. On the other hand, if NDI is configured for indication of newdata an implicit HARQ-ACK signaling is assumed on the UE side.

However, as shown in FIG. 8 , in some embodiments where errors postPUSCH decoding are found, and a gNB has enough resources for processingthe defined UL semantic error correction steps from above an indicationas part of a RAN-embedded signaling mechanism may signal the latter gNBdecision to a UE to optimize the UE processing and operation costs. Forinstance, in case of a semi-statically RRC configured grant (“CG”) 802,either semi-statically signaled/enabled as a Type I CG (by means of RRCsignaling) or dynamically signaled, enabled/disabled as Type II CG (bymeans of DCI Format 0), the gNB can additionally signal to the UE anexplicit HARQ feedback tuple (NACK, SEC_ON) 804 as a bit field of DCIassociated with the HARQ process number of the PUSCH erroneoustransmission 806. The tuple (NACK, SEC_ON) 804 shall explicitly indicateto the UE the fact that the gNB received the UL PUSCH video coded datawith errors (e.g., as a NACK at syntactic level), but upon enablement ofsemantic error correction, a video approximate version of the originalmessage can be recovered within the QoS flow requirements of theassociated DRB within sufficiently low video distortion of semanticapproximation compared to a given and/or known fixed threshold. Thus,the explicit HARQ signaling tuple (NACK, SEC_ON) 804 represents animplicit HARQ-ACK based on RAN-level support for the video approximatesemantic communications that is intended to optimize energy andprocessing costs, as well as resource allocation, of a UE wherebyautonomous retransmissions 812 may be configured and enabled by means ofone or more CG configurations (either as Type-I or Type-II,respectively).

The tuple signaling implicit HARQ-ACK for video approximate semanticcommunications is meant in some embodiments to dynamically extend a UE'scurrent CG retransmission timer 808 for the associated HARQ processnumber by a known fixed duration δ_(SEC) 810. In an embodiment, δ_(SEC)810 is set up semi-statically by at least one of RRC configuration, anda MAC-CE configuration, to allow the RAN level semantic error correctionprocessing to take place within its expected processing delay <δ_(SEC)810. Upon successful completion of the semantic error correctionprocedure at the RAN-level, in some embodiments, the gNB can indicate tothe UE to schedule new video coded data onto the next CG 802 by means ofan explicit downlink HARQ-ACK feedback information at least in the formof one of a DCI Format 0 signaling NDI request for the current HARQprocess number under the currently active CG configuration, a dynamiccombination of a first DCI CG deactivation followed by a second DCI CGactivation for Type-II CGI, a reset indication over DCI PDCCH signalingfor the CG state and associated transmission and retransmission timers808 for both Type-I and Type-II CG types.

This mechanism, in one embodiment, enables the gNB to control the UEoperation and optimize its resource utilization with respect to energyusage, radio resource usage by the HARQ process handling video codedtraffic data wherein semantic error correction and video approximatesemantic communications modes are dynamically enabled at the RAN side.FIG. 8 illustrates the basic high-level signaling mechanisms involvedbetween a gNB and a UE for such embodiments.

In some embodiments, the HARQ feedback tuple (NACK, SEC_ON) 804 can bedelay-aware to additionally include a gNB specified dynamic value toextend the CG retransmission timer 808 of an associated HARQ process,e.g., an updated CG retransmission timer 814. In such an example the gNBmay determine and optimize the duration δ_(SEC) 810 as δ_(SEC) ^(gNB) toproduce the enhanced delay-aware HARQ feedback tuple (NACK, SEC_ON,δ_(SEC) ^(gNB)) as a bitfield based on the RAN knowledge of schedulingupcoming grants, CG active configuration, processing load and delay ofrequired semantic error correction procedures.

In an embodiment, a UE can be configured with at least tworetransmission timers (e.g., cg-RetransmissionTimer (e.g., as defined in3GPP Technical Specification TS 38.321 (V16.3.0—January 2021). 5G; NR;Medium Access Control (MAC) protocol specification (Release 16); and3GPP Technical Specification TS 38.331 (V16.1.0—July 2020). 5G; NR;Radio Resource Control (RRC); Protocol specification (Release 16)) forUL transmissions in a configured grant:

-   -   A first retransmission timer is associated with/applied for UL        transmissions that do not correspond to semantic error        correction and video approximate semantic communications mode;        and    -   A second retransmission timer is associated with/applied for UL        transmissions that correspond to semantic error correction and        video approximate semantic communications mode.

In an example, a PUSCH transmission on a CG resource can include anindication to the network indicating that whether the PUSCH transmissionis a transmission for which gNB may apply semantic error correction andvideo approximate semantic communications mode or whether the PUSCHtransmission is a video transmission. The UE may start the second timerafter an UL transmission that is indicated for which gNB may applysemantic error correction and video approximate semantic communicationsmode on a CG resource.

In an embodiment, a UE, for a configured grant configuration (e.g.,ConfiguredGrantConfig, (e.g., as defined in 3GPP Technical SpecificationTS 38.331 (V16.1.0—July 2020). 5G; NR; Radio Resource Control (RRC);Protocol specification (Release 16)), can be configured with a firstcg-minDFI-Delay and a second cg-minDFI-Delay, wherein the firstcg-minDFI-Delay is applicable to PUSCH transmissions for which gNB mayapply semantic error correction and video approximate semanticcommunications mode, and wherein the second cg-minDFI-Delay isapplicable to PUSCH transmissions for which semantic error correctionand video approximate semantic communications mode are not applicable atgNB.

The above two embodiments may be needed in case the gNB dynamically(e.g., by MAC-CE or DCI or via a timer) can enable/disable semanticerror correction and video approximate semantic communications mode forUL transmissions (e.g., UL transmissions associated with a particularconfigured grant configurations). One reason of such dynamicenabling/disabling could be the dynamic nature of processing/trafficload at gNB. In an implementation, a UE might be configured withmultiple configured grant configurations, and semantic error correctionand video approximate semantic communications mode for UL transmissionscan be enabled/disabled semi-statically per configured grantconfiguration. In an implementation, semantic error correction and videoapproximate semantic communications mode for UL transmissions can besupported for a subset of configured grant configurations with existingspecifications (e.g., of Rel-17 3GPP specifications).

FIG. 9 depicts a user equipment apparatus 900 that may be used for radioaccess network configuration for video approximate semanticcommunications, according to embodiments of the disclosure. In variousembodiments, the user equipment apparatus 900 is used to implement oneor more of the solutions described above. The user equipment apparatus900 may be one embodiment of the remote unit 105 and/or the UE,described above. Furthermore, the user equipment apparatus 900 mayinclude a processor 905, a memory 910, an input device 915, an outputdevice 920, and a transceiver 925.

In some embodiments, the input device 915 and the output device 920 arecombined into a single device, such as a touchscreen. In certainembodiments, the user equipment apparatus 900 may not include any inputdevice 915 and/or output device 920. In various embodiments, the userequipment apparatus 900 may include one or more of: the processor 905,the memory 910, and the transceiver 925, and may not include the inputdevice 915 and/or the output device 920.

As depicted, the transceiver 925 includes at least one transmitter 930and at least one receiver 935. In some embodiments, the transceiver 925communicates with one or more cells (or wireless coverage areas)supported by one or more base units 121. In various embodiments, thetransceiver 925 is operable on unlicensed spectrum. Moreover, thetransceiver 925 may include multiple UE panel supporting one or morebeams. Additionally, the transceiver 925 may support at least onenetwork interface 940 and/or application interface 945. The applicationinterface(s) 945 may support one or more APIs. The network interface(s)940 may support 3GPP reference points, such as Uu, N1, PCS, etc. Othernetwork interfaces 940 may be supported, as understood by one ofordinary skill in the art.

The processor 905, in one embodiment, may include any known controllercapable of executing computer-readable instructions and/or capable ofperforming logical operations. For example, the processor 905 may be amicrocontroller, a microprocessor, a central processing unit (“CPU”), agraphics processing unit (“GPU”), an auxiliary processing unit, a fieldprogrammable gate array (“FPGA”), or similar programmable controller. Insome embodiments, the processor 905 executes instructions stored in thememory 910 to perform the methods and routines described herein. Theprocessor 905 is communicatively coupled to the memory 910, the inputdevice 915, the output device 920, and the transceiver 925. In certainembodiments, the processor 905 may include an application processor(also known as “main processor”) which manages application-domain andoperating system (“OS”) functions and a baseband processor (also knownas “baseband radio processor”) which manages radio functions.

In various embodiments, the processor 905 and transceiver 925 controlthe user equipment apparatus 900 to implement the above described UEbehaviors. In one embodiment, the transceiver 925 receives from atransmitter a bitstream corresponding to a video coded data transmissionwherein the received bitstream includes bitwise transmission errors. Inone embodiment, the processor 905 that performs forward error correction(“FEC”) decoding and correcting at least one bitwise transmission errorof the video coded data transmission whereas at least one bitwisetransmission error is left in a bit-inexact reception of the video codeddata transmissions post FEC decoding.

In one embodiment, the processor 905 applies, by a smart video decoderin a video approximate semantic communications mode, semantic errorcorrection to decoded video coded data transmissions to correct andconceal one or more video artifacts in response to the bit-inexactreception of the video coded data transmissions post FEC decoding. Inone embodiment, the processor 905 reconstructs a video uncodedrepresentation of concealed approximate semantic content relative to thereceived bitstream corresponding to the video coded data transmission.

In one embodiment, the smart video decoder is comprised of a firstfunctionality that decodes the video coded data transmissions accordingto a fixed knowledge base of a video codec specification and a secondfunctionality that provides the semantic error correction by processingthe video decoded information to correct and conceal the one or morevideo artifacts due to the bit-inexact reception of the video coded datatransmissions.

In one embodiment, the video decoding and semantic error correctionfunctionality of the smart video decoder is comprised of one of a videodecoder of the video codec specification, a collection of statisticaljoint spatio-temporal video frame information and a usage of thespatio-temporal video frame information as a first statistical priorsemantic model together with a second statistical model for semanticerror correction and a joint optimization of said video decoding andsemantic error correction functionality as a unique statistical neuralmodel given a fixed knowledge base of the video codec specification.

In one embodiment, the transceiver 925 signals to a transmitter a set ofsmart video decoder capabilities and features in support of the videoapproximate semantic communications mode, the signal comprising at leastone selected from the group of an enablement flag as a one-bit indicatordescribing the enablement state of the semantic error correctionfunctionality for the video approximate semantic communications, amaximum error rate threshold for the amount of transmission errors thesemantic error correction functionality can tolerate to achieve a fixedvideo reconstruction quality, a statistical running window configurationover which a transmission error rate statistic is monitored and comparedwith the maximum error rate threshold tolerated by the semantic errorcorrection, a maximum processing delay, wherein the maximum processingdelay can be further split into a video decoding processing delay and avideo semantic error correction processing delay, an estimated averageenergy consumption indicator comprising of a first estimate of averageenergy consumption with semantic error correction enabled and a secondestimate of average energy consumption with semantic error correctiondisabled, a power supply indicator determining the power source type, anindication determining the maximum video frame mobility and video framechange rate that the semantic error correction can process to achieve afixed video reconstruction quality, a standalone operation flag as aone-bit indicator describing the receiver capability to perform semanticerror correction monitoring and enabling or disabling of the semanticerror correction with assistance from the transmitter or withoutassistance from the transmitter.

In one embodiment, the set of capabilities of the receiver to supportthe video approximate semantic communications mode is indicated by atleast one of selected from the group of semi-static Radio ResourceControl (“RRC”) message signaling, dynamic Uplink Control Information(“UCI”) bit field signaling, dynamic UCI scheduling request signaling,and user equipment (“UE”)/device capability reporting signaling.

In one embodiment, the processor 905 reports the maximum error ratethreshold for transmission errors tolerated by the semantic errorcorrection and the associated statistical running window configurationfor monitoring thereof wherein the maximum error rate threshold isexpressed by at least one selected from the group of a transmissionblock error rate (“BLER”) corresponding to a configured granularity oftransmission blocks, a log-likelihood ratio (“LLR”) average statistic oftransmission blocks post FEC decoding, and a video coded NetworkAbstraction Layer (“NAL”) unit error rate (“NALuER”) average statisticwhereby video coded traffic-aware communications is configured.

In one embodiment, the processor 905 performs one of dynamicallyenabling and dynamically disabling capabilities of the video approximatesemantic communications mode based on the enablement flag indicator ofsemantic error correction functionality wherein the enablement flagindicator status is modified by at least one of a transmitter byindication of at least one selected from the group of downlink controlinformation (“DCI”) bit field message signaling, a DCI signaling for adata communication over a Physical Downlink Shared Channel (“PDSCH”),and Medium Access Control-Control Element (“MAC-CE”) bit field messagesignaling, and the receiver by indication of at least one selected fromthe group of a UCI bit field message signaling, a UCI signaling for adata communication over a Physical Uplink Shared Channel (“PUSCH”), andMAC-CE bit field message signaling.

In one embodiment, one of the dynamic enabling and dynamic disabling ofthe video approximate semantic communications mode is transientlydetermined spanning a fixed duration of a countdown timer over which thesemantic error correction is enabled or disabled.

In one embodiment, an energy-aware receiver signals to the transmitterone of dynamic enabling and dynamic disabling of the semantic errorcorrection capability given at least one of a critical battery energythreshold such that the semantic error correction capability is at leastpartially disabled in response to the battery energy level droppingbelow the critical battery energy threshold and the semantic errorcorrection capability is enabled in response to the battery energy levelsatisfying the critical battery energy threshold wherein a reason for adynamic change in the enablement status of the semantic error correctioncapability is jointly reported with an associated enablement and/ordisablement command, and a power supply status change such that adisablement indication is signaled in response to a battery energy flowpowering the receiver and an enablement indication is signaled inresponse to an external energy source flow powering the receiver whereina reason for a dynamic change in the enablement status of the semanticerror correction capability is jointly reported with an associatedenablement and/or disablement command.

In one embodiment, the transceiver 925 receives additional assistance incontrolling the video approximate semantic communications mode and errorconcealment from the transmitter by means of at least one selected fromthe group of a delay-aware predictive scheduling of one or moreon-demand video keyframes on behalf of the receiver to conceal andprevent video errors propagation, a multi-layered video codedtraffic-aware opportunistic dropping of at least one video coded layerinformation to prevent video errors, and a monitoring and determining ofa transmissions error statistic and enabling or disabling of thesemantic error correction within a configured statistical running windowwherein the transceiver 925 processes a hybrid automatic repeat request(“HARQ”) process and provides a HARQ acknowledgement (“HARQ-ACK”) orHARQ non-acknowledgement (“HARQ-NACK”) feedback to the transmitterthereof.

In one embodiment, in response to the determined transmissions errorstatistic being less than a configured receiver capability of themaximum error rate threshold, no retransmissions are necessary to bereceived by the transceiver wherein the transceiver receives dynamicindication to perform semantic error correction from the transmitter byat least one selected from the group of a bit field indication withinDemodulation Reference Signal (“DM-RS”) embedded in the originallytransmitted transmission blocks within a PDSCH, a dedicated DCI bitfield signaling over a Physical Downlink Control Channel (“PDCCH”), anda MAC-CE indication.

In one embodiment, in response to the determined transmissions errorstatistic being equal to or greater than a configured receivercapability of the maximum error rate threshold, retransmissions arenecessary to be received by the transceiver to aid the transceiver inone of lowering the transmissions error statistic below the receivercapability of the maximum error rate threshold for transmission errorsthat the semantic error correction functionality can tolerate to achievea fixed video reconstruction quality and eliminating the transmissionserrors post FEC decoding.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the apparatus 900 independently controls the videoapproximate semantic communications mode by monitoring and determining atransmissions error statistic that triggers the semantic errorcorrection enabling and/or disabling within its configured statisticalrunning window and signaling appropriate units of HARQ feedback to thetransmitter given the internal operation mode of the semantic errorcorrection.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the processor 905 quantizes the second component of aunit of HARQ feedback information to a discrete number of confidencelevels such that a first HARQ feedback component as a NACK coupled witha second HARQ feedback component as a lowest confidence level representsa transmission wherein the remaining uncoded video artifacts of thebit-inexact transmission are semantically correctable and concealable bythe enabled receiver semantic error correction processing.

In one embodiment, the apparatus 900 is part of a Radio Access Network(“RAN”) as one of a plurality of transmission-reception points whereinthe apparatus 900 and/or the enclosing RAN supports the videoapproximate semantic communications mode for semantic error correction.

In one embodiment, the apparatus 900 signals an explicit unit ofHARQ-NACK feedback formed of a tuple of two components as a bit field, afirst component corresponding to an associated NACK indication and asecond component corresponding to an indication of the active status ofthe video approximate semantic communications mode whereby the unit ofHARQ-NACK feedback signals to a transmitter the extension of aretransmission timer of configured grants (“CGs”) to allow for thesemantic error correction processing delay of the receiver by one of afixed delay duration δ_(SEC) and a dynamic delay duration δ_(SEC) ^(gNB)determined based on the receiver knowledge of processing semantic errorcorrection delay and the time span to the next available configuredgrant occasion, whereby the determined δ_(SEC) ^(gNB) extends theHARQ-NACK feedback tuple bit field as a third component.

The memory 910, in one embodiment, is a computer readable storagemedium. In some embodiments, the memory 910 includes volatile computerstorage media. For example, the memory 910 may include a RAM, includingdynamic RAM (“DRAM”), synchronous dynamic RAM (“SDRAM”), and/or staticRAM (“SRAM”). In some embodiments, the memory 910 includes non-volatilecomputer storage media. For example, the memory 910 may include a harddisk drive, a flash memory, or any other suitable non-volatile computerstorage device. In some embodiments, the memory 910 includes bothvolatile and non-volatile computer storage media.

In some embodiments, the memory 910 stores data related to radio accessnetwork configuration for video approximate semantic communications. Forexample, the memory 910 may store various parameters, panel/beamconfigurations, resource assignments, policies, and the like asdescribed above. In certain embodiments, the memory 910 also storesprogram code and related data, such as an operating system or othercontroller algorithms operating on the user equipment apparatus 900.

The input device 915, in one embodiment, may include any known computerinput device including a touch panel, a button, a keyboard, a stylus, amicrophone, or the like. In some embodiments, the input device 915 maybe integrated with the output device 920, for example, as a touchscreenor similar touch-sensitive display. In some embodiments, the inputdevice 915 includes a touchscreen such that text may be input using avirtual keyboard displayed on the touchscreen and/or by handwriting onthe touchscreen. In some embodiments, the input device 915 includes twoor more different devices, such as a keyboard and a touch panel.

The output device 920, in one embodiment, is designed to output visual,audible, and/or haptic signals. In some embodiments, the output device920 includes an electronically controllable display or display devicecapable of outputting visual data to a user. For example, the outputdevice 920 may include, but is not limited to, an LCD display, an LEDdisplay, an OLED display, a projector, or similar display device capableof outputting images, text, or the like to a user. As another,non-limiting, example, the output device 920 may include a wearabledisplay separate from, but communicatively coupled to, the rest of theuser equipment apparatus 900, such as a smart watch, smart glasses, aheads-up display, or the like. Further, the output device 920 may be acomponent of a smart phone, a personal digital assistant, a television,a table computer, a notebook (laptop) computer, a personal computer, avehicle dashboard, or the like.

In certain embodiments, the output device 920 includes one or morespeakers for producing sound. For example, the output device 920 mayproduce an audible alert or notification (e.g., a beep or chime). Insome embodiments, the output device 920 includes one or more hapticdevices for producing vibrations, motion, or other haptic feedback. Insome embodiments, all, or portions of the output device 920 may beintegrated with the input device 915. For example, the input device 915and output device 920 may form a touchscreen or similar touch-sensitivedisplay. In other embodiments, the output device 920 may be located nearthe input device 915.

The transceiver 925 communicates with one or more network functions of amobile communication network via one or more access networks. Thetransceiver 925 operates under the control of the processor 905 totransmit messages, data, and other signals and also to receive messages,data, and other signals. For example, the processor 905 may selectivelyactivate the transceiver 925 (or portions thereof) at particular timesin order to send and receive messages.

The transceiver 925 includes at least transmitter 930 and at least onereceiver 935. One or more transmitters 930 may be used to provide ULcommunication signals to a base unit 121, such as the UL transmissionsdescribed herein. Similarly, one or more receivers 935 may be used toreceive DL communication signals from the base unit 121, as describedherein. Although only one transmitter 930 and one receiver 935 areillustrated, the user equipment apparatus 900 may have any suitablenumber of transmitters 930 and receivers 935. Further, thetransmitter(s) 930 and the receiver(s) 935 may be any suitable type oftransmitters and receivers. In one embodiment, the transceiver 925includes a first transmitter/receiver pair used to communicate with amobile communication network over licensed radio spectrum and a secondtransmitter/receiver pair used to communicate with a mobilecommunication network over unlicensed radio spectrum.

In certain embodiments, the first transmitter/receiver pair used tocommunicate with a mobile communication network over licensed radiospectrum and the second transmitter/receiver pair used to communicatewith a mobile communication network over unlicensed radio spectrum maybe combined into a single transceiver unit, for example a single chipperforming functions for use with both licensed and unlicensed radiospectrum. In some embodiments, the first transmitter/receiver pair andthe second transmitter/receiver pair may share one or more hardwarecomponents. For example, certain transceivers 925, transmitters 930, andreceivers 935 may be implemented as physically separate components thataccess a shared hardware resource and/or software resource, such as forexample, the network interface 940.

In various embodiments, one or more transmitters 930 and/or one or morereceivers 935 may be implemented and/or integrated into a singlehardware component, such as a multi-transceiver chip, asystem-on-a-chip, an application-specific integrated circuit (“ASIC”),or other type of hardware component. In certain embodiments, one or moretransmitters 930 and/or one or more receivers 935 may be implementedand/or integrated into a multi-chip module. In some embodiments, othercomponents such as the network interface 940 or other hardwarecomponents/circuits may be integrated with any number of transmitters930 and/or receivers 935 into a single chip. In such embodiment, thetransmitters 930 and receivers 935 may be logically configured as atransceiver 925 that uses one more common control signals or as modulartransmitters 930 and receivers 935 implemented in the same hardware chipor in a multi-chip module.

FIG. 10 depicts a network apparatus 1000 that may be used for radioaccess network configuration for video approximate semanticcommunications, according to embodiments of the disclosure. In oneembodiment, network apparatus 1000 may be one implementation of a RANnode, such as the base unit 121, the RAN node 210, or gNB, describedabove. Furthermore, the base network apparatus 1000 may include aprocessor 1005, a memory 1010, an input device 1015, an output device1020, and a transceiver 1025.

In some embodiments, the input device 1015 and the output device 1020are combined into a single device, such as a touchscreen. In certainembodiments, the network apparatus 1000 may not include any input device1015 and/or output device 1020. In various embodiments, the networkapparatus 1000 may include one or more of: the processor 1005, thememory 1010, and the transceiver 1025, and may not include the inputdevice 1015 and/or the output device 1020.

As depicted, the transceiver 1025 includes at least one transmitter 1030and at least one receiver 1035. Here, the transceiver 1025 communicateswith one or more remote units 105. Additionally, the transceiver 1025may support at least one network interface 1040 and/or applicationinterface 1045. The application interface(s) 1045 may support one ormore APIs. The network interface(s) 1040 may support 3GPP referencepoints, such as Uu, N1, N2 and N3. Other network interfaces 1040 may besupported, as understood by one of ordinary skill in the art.

The processor 1005, in one embodiment, may include any known controllercapable of executing computer-readable instructions and/or capable ofperforming logical operations. For example, the processor 1005 may be amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or similar programmable controller. In some embodiments,the processor 1005 executes instructions stored in the memory 1010 toperform the methods and routines described herein. The processor 1005 iscommunicatively coupled to the memory 1010, the input device 1015, theoutput device 1020, and the transceiver 1025. In certain embodiments,the processor 1005 may include an application processor (also known as“main processor”) which manages application-domain and operating system(“OS”) functions and a baseband processor (also known as “baseband radioprocessor”) which manages radio function.

The memory 1010, in one embodiment, is a computer readable storagemedium. In some embodiments, the memory 1010 includes volatile computerstorage media. For example, the memory 1010 may include a RAM, includingDRAM, SDRAM, and/or SRAM. In some embodiments, the memory 1010 includesnon-volatile computer storage media. For example, the memory 1010 mayinclude a hard disk drive, a flash memory, or any other suitablenon-volatile computer storage device. In some embodiments, the memory1010 includes both volatile and non-volatile computer storage media.

In some embodiments, the memory 1010 stores data related to radio accessnetwork configuration for video approximate semantic communications. Forexample, the memory 1010 may store parameters, configurations, resourceassignments, policies, and the like, as described above. In certainembodiments, the memory 1010 also stores program code and related data,such as an operating system or other controller algorithms operating onthe network apparatus 1000.

The input device 1015, in one embodiment, may include any known computerinput device including a touch panel, a button, a keyboard, a stylus, amicrophone, or the like. In some embodiments, the input device 1015 maybe integrated with the output device 1020, for example, as a touchscreenor similar touch-sensitive display. In some embodiments, the inputdevice 1015 includes a touchscreen such that text may be input using avirtual keyboard displayed on the touchscreen and/or by handwriting onthe touchscreen. In some embodiments, the input device 1015 includes twoor more different devices, such as a keyboard and a touch panel.

The output device 1020, in one embodiment, is designed to output visual,audible, and/or haptic signals. In some embodiments, the output device1020 includes an electronically controllable display or display devicecapable of outputting visual data to a user. For example, the outputdevice 1020 may include, but is not limited to, an LCD display, an LEDdisplay, an OLED display, a projector, or similar display device capableof outputting images, text, or the like to a user. As another,non-limiting, example, the output device 1020 may include a wearabledisplay separate from, but communicatively coupled to, the rest of thenetwork apparatus 1000, such as a smart watch, smart glasses, a heads-updisplay, or the like. Further, the output device 1020 may be a componentof a smart phone, a personal digital assistant, a television, a tablecomputer, a notebook (laptop) computer, a personal computer, a vehicledashboard, or the like.

In certain embodiments, the output device 1020 includes one or morespeakers for producing sound. For example, the output device 1020 mayproduce an audible alert or notification (e.g., a beep or chime). Insome embodiments, the output device 1020 includes one or more hapticdevices for producing vibrations, motion, or other haptic feedback. Insome embodiments, all, or portions of the output device 1020 may beintegrated with the input device 1015. For example, the input device1015 and output device 1020 may form a touchscreen or similartouch-sensitive display. In other embodiments, the output device 1020may be located near the input device 1015.

The transceiver 1025 includes at least transmitter 1030 and at least onereceiver 1035. One or more transmitters 1030 may be used to communicatewith the UE, as described herein. Similarly, one or more receivers 1035may be used to communicate with network functions in the non-publicnetwork (“NPN”), PLMN and/or RAN, as described herein. Although only onetransmitter 1030 and one receiver 1035 are illustrated, the networkapparatus 1000 may have any suitable number of transmitters 1030 andreceivers 1035. Further, the transmitter(s) 1030 and the receiver(s)1035 may be any suitable type of transmitters and receivers.

In one embodiment, the transceiver 1025 receives an indication of videoapproximate semantic communications mode of a receiver and aconfiguration thereof and transmits a plurality of video coded datatransmissions. In one embodiment, the processor 1005 uses theconfiguration of video approximate semantic communications mode of thereceiver to process HARQ feedback monitoring and to signal forenablement/disablement of semantic error correction at the receiver.

FIG. 11 is a flowchart diagram of a method 1100 for radio access networkconfiguration for video approximate semantic communications. The method1100 may be performed by a network entity such as a base node, a gNB,and/or the network equipment apparatus 1000 or by a remote unit 105 suchas a UE or a user equipment apparatus 900. In some embodiments, themethod 1100 may be performed by a processor executing program code, forexample, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliaryprocessing unit, a FPGA, or the like.

In one embodiment, the method 1100 includes receiving 1105 from atransmitter a bitstream corresponding to a video coded data transmissionwherein the received bitstream includes bitwise transmission errors. Inone embodiment, the method 1100 includes performing 1110 forward errorcorrection (“FEC”) decoding and correcting at least one bitwisetransmission error of the video coded data transmission whereas at leastone bitwise transmission error is left in a bit-inexact reception of thevideo coded data transmissions post FEC decoding.

In one embodiment, the method 1100 includes applying 1115, by a smartvideo decoder in a video approximate semantic communications mode,semantic error correction to decoded video coded data transmissions tocorrect and conceal one or more video artifacts in response to thebit-inexact reception of the video coded data transmissions post FECdecoding. In one embodiment, the method 1100 includes reconstructing1120 a video uncoded representation of concealed approximate semanticcontent relative to the received bitstream corresponding to the videocoded data transmission, and the method 1100 ends.

FIG. 12 is a flowchart diagram of a method 1200 for radio access networkconfiguration for video approximate semantic communications. The method1200 may be performed by a network entity such as a base node, a gNB,and/or the network equipment apparatus 1000 or by a remote unit 105 suchas a UE or a user equipment apparatus 900. In some embodiments, themethod 1200 may be performed by a processor executing program code, forexample, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliaryprocessing unit, a FPGA, or the like.

In one embodiment, the method 1200 includes receiving 1205 an indicationof video approximate semantic communications mode of a receiver and aconfiguration thereof. In one embodiment, the method 1200 includestransmitting 1210 a plurality of video coded data transmissions. In oneembodiment, the method 1200 includes using 1215 the configuration ofvideo approximate semantic communications mode of the receiver toprocess HARQ feedback monitoring and to signal forenablement/disablement of semantic error correction at the receiver, andthe method 1200 ends.

A first apparatus is disclosed for radio access network configurationfor video approximate semantic communications. The first apparatus mayinclude a network entity such as a base node, a gNB, and/or the networkequipment apparatus 1000 or a remote unit 105 such as a UE or a userequipment apparatus 900. In some embodiments, the first apparatusincludes a processor executing program code, for example, amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or the like.

In one embodiment, the first apparatus includes a transceiver thatreceives from a transmitter a bitstream corresponding to a video codeddata transmission wherein the received bitstream includes videoartifacts due to bitwise transmission errors. In one embodiment, thefirst apparatus includes a processor that performs forward errorcorrection (“FEC”) decoding and correcting at least one bitwisetransmission error of the video coded data transmission whereas at leastone bitwise transmission error is left in a bit-inexact reception of thevideo coded data transmissions post FEC decoding.

In one embodiment, the processor applies, by a smart video decoder in avideo approximate semantic communications mode, semantic errorcorrection to decoded video coded data transmissions to correct andconceal one or more video artifacts in response to the bit-inexactreception of the video coded data transmissions post FEC decoding. Inone embodiment, the processor reconstructs a video uncodedrepresentation of concealed approximate semantic content relative to thereceived bitstream corresponding to the video coded data transmission.

In one embodiment, the smart video decoder is comprised of a firstfunctionality that decodes the video coded data transmissions accordingto a fixed knowledge base of a video codec specification and a secondfunctionality that provides the semantic error correction by processingthe video decoded information to correct and conceal the one or morevideo artifacts due to the bit-inexact reception of the video coded datatransmissions.

In one embodiment, the video decoding and semantic error correctionfunctionality of the smart video decoder is comprised of one of a videodecoder of the video codec specification, a collection of statisticaljoint spatio-temporal video frame information and a usage of thespatio-temporal video frame information as a first statistical priorsemantic model together with a second statistical model for semanticerror correction and a joint optimization of said video decoding andsemantic error correction functionality as a unique statistical neuralmodel given a fixed knowledge base of the video codec specification.

In one embodiment, the transceiver signals to a transmitter a set ofsmart video decoder capabilities and features in support of the videoapproximate semantic communications mode, the signal comprising at leastone selected from the group of an enablement flag as a one-bit indicatordescribing the enablement state of the semantic error correctionfunctionality for the video approximate semantic communications, amaximum error rate threshold for the amount of transmission errors thesemantic error correction functionality can tolerate to achieve a fixedvideo reconstruction quality, a statistical running window configurationover which a transmission error rate statistic is monitored and comparedwith the maximum error rate threshold tolerated by the semantic errorcorrection, a maximum processing delay, wherein the maximum processingdelay can be further split into a video decoding processing delay and avideo semantic error correction processing delay, an estimated averageenergy consumption indicator comprising of a first estimate of averageenergy consumption with semantic error correction enabled and a secondestimate of average energy consumption with semantic error correctiondisabled, a power supply indicator determining the power source type, anindication determining the maximum video frame mobility and video framechange rate that the semantic error correction can process to achieve afixed video reconstruction quality, a standalone operation flag as aone-bit indicator describing the receiver capability to perform semanticerror correction monitoring and enabling or disabling of the semanticerror correction with assistance from the transmitter or withoutassistance from the transmitter.

In one embodiment, the set of capabilities of the receiver to supportthe video approximate semantic communications mode is indicated by atleast one of selected from the group of semi-static Radio ResourceControl (“RRC”) message signaling, dynamic Uplink Control Information(“UCI”) bit field signaling, dynamic UCI scheduling request signaling,and user equipment (“UE”)/device capability reporting signaling.

In one embodiment, the processor reports the maximum error ratethreshold for transmission errors tolerated by the semantic errorcorrection and the associated statistical running window configurationfor monitoring thereof wherein the maximum error rate threshold isexpressed by at least one selected from the group of a transmissionblock error rate (“BLER”) corresponding to a configured granularity oftransmission blocks, a log-likelihood ratio (“LLR”) average statistic oftransmission blocks post FEC decoding, and a video coded NetworkAbstraction Layer (“NAL”) unit error rate (“NALuER”) average statisticwhereby video coded traffic-aware communications is configured.

In one embodiment, the processor performs one of dynamically enablingand dynamically disabling capabilities of the video approximate semanticcommunications mode based on the enablement flag indicator of semanticerror correction functionality wherein the enablement flag indicatorstatus is modified by at least one of a transmitter by indication of atleast one selected from the group of downlink control information(“DCI”) bit field message signaling, a DCI signaling for a datacommunication over a Physical Downlink Shared Channel (“PDSCH”), andMedium Access Control-Control Element (“MAC-CE”) bit field messagesignaling, and the receiver by indication of at least one selected fromthe group of a UCI bit field message signaling, a UCI signaling for adata communication over a Physical Uplink Shared Channel (“PUSCH”), andMAC-CE bit field message signaling.

In one embodiment, one of the dynamic enabling and dynamic disabling ofthe video approximate semantic communications mode is transientlydetermined spanning a fixed duration of a countdown timer over which thesemantic error correction is enabled or disabled.

In one embodiment, an energy-aware receiver signals to the transmitterone of dynamic enabling and dynamic disabling of the semantic errorcorrection capability given at least one of a critical battery energythreshold such that the semantic error correction capability is at leastpartially disabled in response to the battery energy level droppingbelow the critical battery energy threshold and the semantic errorcorrection capability is enabled in response to the battery energy levelsatisfying the critical battery energy threshold wherein a reason for adynamic change in the enablement status of the semantic error correctioncapability is jointly reported with an associated enablement and/ordisablement command, and a power supply status change such that adisablement indication is signaled in response to a battery energy flowpowering the receiver and an enablement indication is signaled inresponse to an external energy source flow powering the receiver whereina reason for a dynamic change in the enablement status of the semanticerror correction capability is jointly reported with an associatedenablement and/or disablement command.

In one embodiment, the transceiver receives additional assistance incontrolling the video approximate semantic communications mode and errorconcealment from the transmitter by means of at least one selected fromthe group of a delay-aware predictive scheduling of one or moreon-demand video keyframes on behalf of the receiver to conceal andprevent video errors propagation, a multi-layered video codedtraffic-aware opportunistic dropping of at least one video coded layerinformation to prevent video errors, and a monitoring and determining ofa transmissions error statistic and enabling or disabling of thesemantic error correction within a configured statistical running windowwherein the transceiver processes a hybrid automatic repeat request(“HARQ”) process and provides a HARQ acknowledgement (“HARQ-ACK”) orHARQ non-acknowledgement (“HARQ-NACK”) feedback to the transmitterthereof.

In one embodiment, in response to the determined transmissions errorstatistic being less than a configured receiver capability of themaximum error rate threshold, no retransmissions are necessary to bereceived by the transceiver wherein the transceiver receives dynamicindication to perform semantic error correction from the transmitter byat least one selected from the group of a bit field indication withinDemodulation Reference Signal (“DM-RS”) embedded in the originallytransmitted transmission blocks within a PDSCH, a dedicated DCI bitfield signaling over a Physical Downlink Control Channel (“PDCCH”), anda MAC-CE indication.

In one embodiment, in response to the determined transmissions errorstatistic being equal to or greater than a configured receivercapability of the maximum error rate threshold, retransmissions arenecessary to be received by the transceiver to aid the transceiver inone of lowering the transmissions error statistic below the receivercapability of the maximum error rate threshold for transmission errorsthat the semantic error correction functionality can tolerate to achievea fixed video reconstruction quality and eliminating the transmissionserrors post FEC decoding.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the apparatus independently controls the videoapproximate semantic communications mode by monitoring and determining atransmissions error statistic that triggers the semantic errorcorrection enabling and/or disabling within its configured statisticalrunning window and signaling appropriate units of HARQ feedback to thetransmitter given the internal operation mode of the semantic errorcorrection.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the processor quantizes the second component of aunit of HARQ feedback information to a discrete number of confidencelevels such that a first HARQ feedback component as a NACK coupled witha second HARQ feedback component as a lowest confidence level representsa transmission wherein the remaining uncoded video artifacts of thebit-inexact transmission are semantically correctable and concealable bythe enabled receiver semantic error correction processing.

In one embodiment, the apparatus is part of a Radio Access Network(“RAN”) as one of a plurality of transmission-reception points whereinthe apparatus and/or the enclosing RAN supports the video approximatesemantic communications mode for semantic error correction.

In one embodiment, the apparatus signals an explicit unit of HARQ-NACKfeedback formed of a tuple of two components as a bit field, a firstcomponent corresponding to an associated NACK indication and a secondcomponent corresponding to an indication of the active status of thevideo approximate semantic communications mode whereby the unit ofHARQ-NACK feedback signals to a transmitter the extension of aretransmission timer of configured grants (“CGs”) to allow for thesemantic error correction processing delay of the receiver by one of afixed delay duration δ_(SEC) and a dynamic delay duration δ_(SEC) ^(gNB)determined based on the receiver knowledge of processing semantic errorcorrection delay and the time span to the next available configuredgrant occasion, whereby the determined δ_(SEC) ^(gNB) extends theHARQ-NACK feedback tuple bit field as a third component.

A first method is disclosed for radio access network configuration forvideo approximate semantic communications. The first method may beperformed by a network entity such as a base node, a gNB, and/or thenetwork equipment apparatus 1000 or by a remote unit 105 such as a UE ora user equipment apparatus 900. In some embodiments, the first methodmay be performed by a processor executing program code, for example, amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or the like.

In one embodiment, the first method includes receiving from atransmitter a bitstream corresponding to a video coded data transmissionwherein the received bitstream includes bitwise transmission errors. Inone embodiment, the first method includes performing forward errorcorrection (“FEC”) decoding and correcting at least one bitwisetransmission error of the video coded data transmission whereas at leastone bitwise transmission error is left in a bit-inexact reception of thevideo coded data transmissions post FEC decoding.

In one embodiment, the first method includes applying, by a smart videodecoder in a video approximate semantic communications mode, semanticerror correction to decoded video coded data transmissions to correctand conceal one or more video artifacts in response to the bit-inexactreception of the video coded data transmissions post FEC decoding. Inone embodiment, the first method includes reconstructing a video uncodedrepresentation of concealed approximate semantic content relative to thereceived bitstream corresponding to the video coded data transmission.

In one embodiment, the smart video decoder is comprised of a firstfunctionality that decodes the video coded data transmissions accordingto a fixed knowledge base of a video codec specification and a secondfunctionality that provides the semantic error correction by processingthe video decoded information to correct and conceal the one or morevideo artifacts due to the bit-inexact reception of the video coded datatransmissions.

In one embodiment, the video decoding and semantic error correctionfunctionality of the smart video decoder is comprised of one of a videodecoder of the video codec specification, a collection of statisticaljoint spatio-temporal video frame information and a usage of thespatio-temporal video frame information as a first statistical priorsemantic model together with a second statistical model for semanticerror correction and a joint optimization of said video decoding andsemantic error correction functionality as a unique statistical neuralmodel given a fixed knowledge base of the video codec specification.

In one embodiment, the first method includes signaling to a transmittera set of smart video decoder capabilities and features in support of thevideo approximate semantic communications mode, the signal comprising atleast one selected from the group of an enablement flag as a one-bitindicator describing the enablement state of the semantic errorcorrection functionality for the video approximate semanticcommunications, a maximum error rate threshold for the amount oftransmission errors the semantic error correction functionality cantolerate to achieve a fixed video reconstruction quality, a statisticalrunning window configuration over which a transmission error ratestatistic is monitored and compared with the maximum error ratethreshold tolerated by the semantic error correction, a maximumprocessing delay, wherein the maximum processing delay can be furthersplit into a video decoding processing delay and a video semantic errorcorrection processing delay, an estimated average energy consumptionindicator comprising of a first estimate of average energy consumptionwith semantic error correction enabled and a second estimate of averageenergy consumption with semantic error correction disabled, a powersupply indicator determining the power source type, an indicationdetermining the maximum video frame mobility and video frame change ratethat the semantic error correction can process to achieve a fixed videoreconstruction quality, a standalone operation flag as a one-bitindicator describing the receiver capability to perform semantic errorcorrection monitoring and enabling or disabling of the semantic errorcorrection with assistance from the transmitter or without assistancefrom the transmitter.

In one embodiment, the set of capabilities of the receiver to supportthe video approximate semantic communications mode is indicated by atleast one of selected from the group of semi-static Radio ResourceControl (“RRC”) message signaling, dynamic Uplink Control Information(“UCI”) bit field signaling, dynamic UCI scheduling request signaling,and user equipment (“UE”)/device capability reporting signaling.

In one embodiment, the first method includes reporting the maximum errorrate threshold for transmission errors tolerated by the semantic errorcorrection and the associated statistical running window configurationfor monitoring thereof wherein the maximum error rate threshold isexpressed by at least one selected from the group of a transmissionblock error rate (“BLER”) corresponding to a configured granularity oftransmission blocks, a log-likelihood ratio (“LLR”) average statistic oftransmission blocks post FEC decoding, and a video coded NetworkAbstraction Layer (“NAL”) unit error rate (“NALuER”) average statisticwhereby video coded traffic-aware communications is configured.

In one embodiment, the first method includes performing one ofdynamically enabling and dynamically disabling capabilities of the videoapproximate semantic communications mode based on the enablement flagindicator of semantic error correction functionality wherein theenablement flag indicator status is modified by at least one of atransmitter by indication of at least one selected from the group ofdownlink control information (“DCI”) bit field message signaling, a DCIsignaling for a data communication over a Physical Downlink SharedChannel (“PDSCH”), and Medium Access Control-Control Element (“MAC-CE”)bit field message signaling, and the receiver by indication of at leastone selected from the group of a UCI bit field message signaling, a UCIsignaling for a data communication over a Physical Uplink Shared Channel(“PUSCH”), and MAC-CE bit field message signaling.

In one embodiment, one of the dynamic enabling and dynamic disabling ofthe video approximate semantic communications mode is transientlydetermined spanning a fixed duration of a countdown timer over which thesemantic error correction is enabled or disabled.

In one embodiment, an energy-aware receiver signals to the transmitterone of dynamic enabling and dynamic disabling of the semantic errorcorrection capability given at least one of a critical battery energythreshold such that the semantic error correction capability is at leastpartially disabled in response to the battery energy level droppingbelow the critical battery energy threshold and the semantic errorcorrection capability is enabled in response to the battery energy levelsatisfying the critical battery energy threshold wherein a reason for adynamic change in the enablement status of the semantic error correctioncapability is jointly reported with an associated enablement and/ordisablement command, and a power supply status change such that adisablement indication is signaled in response to a battery energy flowpowering the receiver and an enablement indication is signaled inresponse to an external energy source flow powering the receiver whereina reason for a dynamic change in the enablement status of the semanticerror correction capability is jointly reported with an associatedenablement and/or disablement command.

In one embodiment, the first method includes receiving additionalassistance in controlling the video approximate semantic communicationsmode and error concealment from the transmitter by means of at least oneselected from the group of a delay-aware predictive scheduling of one ormore on-demand video keyframes on behalf of the receiver to conceal andprevent video errors propagation, a multi-layered video codedtraffic-aware opportunistic dropping of at least one video coded layerinformation to prevent video errors, and a monitoring and determining ofa transmissions error statistic and enabling or disabling of thesemantic error correction within a configured statistical running windowwherein the transceiver processes a hybrid automatic repeat request(“HARQ”) process and provides a HARQ acknowledgement (“HARQ-ACK”) orHARQ non-acknowledgement (“HARQ-NACK”) feedback to the transmitterthereof.

In one embodiment, in response to the determined transmissions errorstatistic being less than a configured receiver capability of themaximum error rate threshold, no retransmissions are necessary to bereceived by the transceiver wherein the transceiver receives dynamicindication to perform semantic error correction from the transmitter byat least one selected from the group of a bit field indication withinDemodulation Reference Signal (“DM-RS”) embedded in the originallytransmitted transmission blocks within a PDSCH, a dedicated DCI bitfield signaling over a Physical Downlink Control Channel (“PDCCH”), anda MAC-CE indication.

In one embodiment, in response to the determined transmissions errorstatistic being equal to or greater than a configured receivercapability of the maximum error rate threshold, retransmissions arenecessary to be received by the transceiver transmitter to aid thetransceiver in one of lowering the transmissions error statistic belowthe receiver capability of the maximum error rate threshold fortransmission errors that the semantic error correction functionality cantolerate to achieve a fixed video reconstruction quality and eliminatingthe transmissions errors post FEC decoding.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the method independently controls the videoapproximate semantic communications mode by monitoring and determining atransmissions error statistic that triggers the semantic errorcorrection enabling and/or disabling within its configured statisticalrunning window and signaling appropriate units of HARQ feedback to thetransmitter given the internal operation mode of the semantic errorcorrection.

In one embodiment, the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.

In one embodiment, the first method includes quantizing the secondcomponent of a unit of HARQ feedback information to a discrete number ofconfidence levels such that a first HARQ feedback component as a NACKcoupled with a second HARQ feedback component as a lowest confidencelevel represents a transmission wherein the remaining uncoded videoartifacts of the bit-inexact transmission are semantically correctableand concealable by the enabled receiver semantic error correctionprocessing.

In one embodiment, the first method includes a receiver device apparatusthat is part of a Radio Access Network (“RAN”) as one of a plurality oftransmission-reception points wherein the receiver device apparatusand/or the enclosing RAN supports the video approximate semanticcommunications mode for semantic error correction.

In one embodiment, the first method includes signaling an explicit unitof HARQ-NACK feedback formed of a tuple of two components as a bitfield, a first component corresponding to an associated NACK indicationand a second component corresponding to an indication of the activestatus of the video approximate semantic communications mode whereby theunit of HARQ-NACK feedback signals to a transmitter the extension of aretransmission timer of configured grants (“CGs”) to allow for thesemantic error correction processing delay of the receiver by one of afixed delay duration δ_(SEC) and a dynamic delay duration δ_(SEC) ^(gNB)determined based on the receiver knowledge of processing semantic errorcorrection delay and the time span to the next available configuredgrant occasion, whereby the determined δ_(SEC) ^(gNB) extends theHARQ-NACK feedback tuple bit field as a third component.

A second apparatus is disclosed for radio access network configurationfor video approximate semantic communications. The second apparatus mayinclude a remote unit 105 such as a UE or a user equipment apparatus 900or a network entity such as a base node, a gNB, and/or the networkequipment apparatus 1000. In some embodiments, the second apparatusincludes a processor executing program code, for example, amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or the like.

In one embodiment, the second apparatus includes a transceiver thatreceives an indication of video approximate semantic communications modeof a receiver and a configuration thereof and transmits a plurality ofvideo coded data transmissions. In one embodiment, the second apparatusincludes a processor that uses the configuration of video approximatesemantic communications mode of the receiver to process HARQ feedbackmonitoring and to signal for enablement/disablement of semantic errorcorrection at the receiver.

A second method is disclosed for radio access network configuration forvideo approximate semantic communications. The second method may beperformed by a remote unit 105 such as a UE or a user equipmentapparatus 900 or by a network entity such as a base node, a gNB, and/orthe network equipment apparatus 1000. In some embodiments, the secondmethod may be performed by a processor executing program code, forexample, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliaryprocessing unit, a FPGA, or the like.

In one embodiment, the second method includes receiving an indication ofvideo approximate semantic communications mode of a receiver and aconfiguration thereof and transmitting a plurality of video coded datatransmissions. In one embodiment, the second method includes using theconfiguration of video approximate semantic communications mode of thereceiver to process HARQ feedback monitoring and to signal forenablement/disablement of semantic error correction at the receiver.

Embodiments may be practiced in other specific forms. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

1. A receiver device apparatus, the apparatus comprising: a transceiverthat receives from a transmitter a bitstream corresponding to a videocoded data transmission wherein the received bitstream includes bitwisetransmission errors; and a processor that: performs forward errorcorrection (“FEC”) decoding and correcting at least one bitwisetransmission error of the video coded data transmission whereas at leastone bitwise transmission error is left in a bit-inexact reception of thevideo coded data transmissions post FEC decoding; applies, by a smartvideo decoder in a video approximate semantic communications mode,semantic error correction to decoded video coded data transmissions tocorrect and conceal one or more video artifacts in response to thebit-inexact reception of the video coded data transmissions post FECdecoding; and reconstructs a video uncoded representation of concealedapproximate semantic content relative to the received bitstreamcorresponding to the video coded data transmission.
 2. The apparatus ofclaim 1, wherein the smart video decoder is comprised of a firstfunctionality that decodes the video coded data transmissions accordingto a fixed knowledge base of a video codec specification and a secondfunctionality that provides the semantic error correction by processingthe video decoded information to correct and conceal the one or morevideo artifacts due to the bit-inexact reception of the video coded datatransmissions.
 3. The apparatus of claim 2, wherein the video decodingand semantic error correction functionality of the smart video decoderis comprised of one of: a video decoder of the video codecspecification, a collection of statistical joint spatio-temporal videoframe information and a usage of the spatio-temporal video frameinformation as a first statistical prior semantic model together with asecond statistical model for semantic error correction; and a jointoptimization of said video decoding and semantic error correctionfunctionality as a unique statistical neural model given a fixedknowledge base of the video codec specification.
 4. The apparatus ofclaim 1, wherein the transceiver signals to a transmitter a set of smartvideo decoder capabilities and features in support of the videoapproximate semantic communications mode, the signal comprising at leastone selected from the group of: an enablement flag as a one-bitindicator describing the enablement state of the semantic errorcorrection functionality for the video approximate semanticcommunications; a maximum error rate threshold for the amount oftransmission errors the semantic error correction functionality cantolerate to achieve a fixed video reconstruction quality; a statisticalrunning window configuration over which a transmission error ratestatistic is monitored and compared with the maximum error ratethreshold tolerated by the semantic error correction; a maximumprocessing delay, wherein the maximum processing delay can be furthersplit into a video decoding processing delay and a video semantic errorcorrection processing delay; an estimated average energy consumptionindicator comprising of a first estimate of average energy consumptionwith semantic error correction enabled and a second estimate of averageenergy consumption with semantic error correction disabled; a powersupply indicator determining the power source type; an indicationdetermining the maximum video frame mobility and video frame change ratethat the semantic error correction can process to achieve a fixed videoreconstruction quality; and a standalone operation flag as a one-bitindicator describing the receiver capability to perform semantic errorcorrection monitoring and enabling or disabling of the semantic errorcorrection with assistance from the transmitter or without assistancefrom the transmitter.
 5. The apparatus of claim 4, wherein the set ofcapabilities of the receiver to support the video approximate semanticcommunications mode is indicated by at least one selected from the groupof: semi-static Radio Resource Control (“RRC”) message signaling;dynamic Uplink Control Information (“UCI”) bit field signaling; dynamicUCI scheduling request signaling; and user equipment (“UE”)/devicecapability reporting signaling.
 6. The apparatus of claim 5, wherein theprocessor reports the maximum error rate threshold for transmissionerrors tolerated by the semantic error correction and the associatedstatistical running window configuration for monitoring thereof whereinthe maximum error rate threshold is expressed by at least one selectedfrom the group of: a transmission block error rate (“BLER”)corresponding to a configured granularity of transmission blocks; alog-likelihood ratio (“LLR”) average statistic of transmission blockspost FEC decoding; and a video coded Network Abstraction Layer (“NAL”)unit error rate (“NALuER”) average statistic whereby video codedtraffic-aware communications is configured.
 7. The apparatus of claim 6,wherein the processor performs one of dynamically enabling anddynamically disabling capabilities of the video approximate semanticcommunications mode based on the enablement flag indicator of semanticerror correction functionality wherein the enablement flag indicatorstatus is modified by at least one of: a transmitter by indication of atleast one selected from the group of: downlink control information(“DCI”) bit field message signaling; a DCI signaling for a datacommunication over a Physical Downlink Shared Channel (“PDSCH”); andMedium Access Control-Control Element (“MAC-CE”) bit field messagesignaling; and the receiver by indication of at least one selected fromthe group of: a UCI bit field message signaling; a UCI signaling for adata communication over a Physical Uplink Shared Channel (“PUSCH”); andMAC-CE bit field message signaling.
 8. The apparatus of claim 7, whereinthe one of the dynamic enabling and dynamic disabling of the videoapproximate semantic communications mode is transiently determinedspanning a fixed duration of a countdown timer over which the semanticerror correction is enabled or disabled.
 9. The apparatus of claim 7,wherein an energy-aware receiver signals to the transmitter one ofdynamic enabling and dynamic disabling of the semantic error correctioncapability given at least one of: a critical battery energy thresholdsuch that: the semantic error correction capability is at leastpartially disabled in response to the battery energy level droppingbelow the critical battery energy threshold; and the semantic errorcorrection capability is enabled in response to the battery energy levelsatisfying the critical battery energy threshold, wherein a reason for adynamic change in the enablement status of the semantic error correctioncapability is jointly reported with an associated enablement and/ordisablement command; and a power supply status change such that: adisablement indication is signaled in response to a battery energy flowpowering the receiver; and an enablement indication is signaled inresponse to an external energy source flow powering the receiver,wherein a reason for a dynamic change in the enablement status of thesemantic error correction capability is jointly reported with anassociated enablement and/or disablement command.
 10. The apparatus ofclaim 7, wherein the transceiver receives additional assistance incontrolling the video approximate semantic communications mode and errorconcealment from the transmitter by means of at least one selected fromthe group of: a delay-aware predictive scheduling of one or moreon-demand video keyframes on behalf of the receiver to conceal andprevent video errors propagation; a multi-layered video codedtraffic-aware opportunistic dropping of at least one video coded layerinformation to prevent video errors; and a monitoring and determining ofa transmissions error statistic and enabling or disabling of thesemantic error correction within a configured statistical running windowwherein the transceiver processes a hybrid automatic repeat request(“HARQ”) process and provides a HARQ acknowledgement (“HARQ-ACK”) orHARQ non-acknowledgement (“HARQ-NACK”) feedback to the transmitterthereof.
 11. The apparatus of claim 10, wherein, in response to thedetermined transmissions error statistic being less than a configuredreceiver capability of the maximum error rate threshold, noretransmissions are necessary to be received by the transceiver whereinthe transceiver receives dynamic indication to perform semantic errorcorrection from the transmitter by at least one selected from the groupof: a bit field indication within Demodulation Reference Signal(“DM-RS”) embedded in the originally transmitted transmission blockswithin a PDSCH; a dedicated DCI bit field signaling over a PhysicalDownlink Control Channel (“PDCCH”); and a MAC-CE indication.
 12. Theapparatus of claim 10, wherein, in response to the determinedtransmissions error statistic being equal to or greater than aconfigured receiver capability of the maximum error rate threshold,retransmissions are necessary to be received by the transceiver to aidthe transceiver in one of: lowering the transmissions error statisticbelow the receiver capability of the maximum error rate threshold fortransmission errors that the semantic error correction functionality cantolerate to achieve a fixed video reconstruction quality; andeliminating the transmissions errors post FEC decoding.
 13. Theapparatus of claim 1, wherein the transceiver provides to thetransmitter a unit of HARQ feedback information, wherein the HARQfeedback information is comprised of an information tuple represented asa bit field wherein a first component is a HARQ acknowledgment(“ACK”)/non-acknowledgement (“NACK”) bit determined by completion of FECdecoding of a unit of a transmission block, and a second componentrepresents a bit encoding of a confidence level describing the firstcomponent determination.
 14. The apparatus of claim 1, wherein theapparatus independently controls the video approximate semanticcommunications mode by monitoring and determining a transmissions errorstatistic that triggers the semantic error correction enabling and/ordisabling within its configured statistical running window and signalingappropriate units of HARQ feedback to the transmitter given the internaloperation mode of the semantic error correction.
 15. The apparatus ofclaim 14, wherein the transceiver provides to the transmitter a unit ofHARQ feedback information, wherein the HARQ feedback information iscomprised of an information tuple represented as a bit field wherein afirst component is a HARQ acknowledgment (“ACK”)/non-acknowledgement(“NACK”) bit determined by completion of FEC decoding of a unit of atransmission block, and a second component represents a bit encoding ofa confidence level describing the first component determination.
 16. Theapparatus of claim 15, wherein the processor quantizes the secondcomponent of a unit of HARQ feedback information to a discrete number ofconfidence levels such that a first HARQ feedback component as a NACKcoupled with a second HARQ feedback component as a lowest confidencelevel represents a transmission wherein the remaining uncoded videoartifacts of the bit-inexact transmission are semantically correctableand concealable by the enabled receiver semantic error correctionprocessing.
 17. The apparatus of claim 3, wherein the apparatus is partof a Radio Access Network (“RAN”) as one of a plurality oftransmission-reception points wherein the apparatus and/or the enclosingRAN supports the video approximate semantic communications mode forsemantic error correction.
 18. The apparatus of claim 17, wherein theapparatus signals an explicit unit of HARQ-NACK feedback formed of atuple of two components as a bit field, a first component correspondingto an associated NACK indication and a second component corresponding toan indication of the active status of the video approximate semanticcommunications mode whereby the unit of HARQ-NACK feedback signals to atransmitter the extension of a retransmission timer of configured grants(“CGs”) to allow for the semantic error correction processing delay ofthe receiver by one of: a fixed delay duration δ_(SEC); and a dynamicdelay duration δ_(SEC) ^(gNB) determined based on the receiver knowledgeof processing semantic error correction delay and the time span to thenext available configured grant occasion, whereby the determined δ_(SEC)^(gNB) extends the HARQ-NACK feedback tuple bit field as a thirdcomponent.
 19. A method at a receiver device, the method comprising:receiving from a transmitter a bitstream corresponding to a video codeddata transmission wherein the received bitstream includes bitwisetransmission errors; performing forward error correction (“FEC”)decoding and correcting at least one bitwise transmission error of thevideo coded data transmission whereas at least one bitwise transmissionerror is left in a bit-inexact reception of the video coded datatransmissions post FEC decoding; applying, by a smart video decoder in avideo approximate semantic communications mode, semantic errorcorrection to decoded video coded data transmissions to correct andconceal one or more video artifacts in response to the bit-inexactreception of the video coded data transmissions post FEC decoding; andreconstructing a video uncoded representation of concealed approximatesemantic content relative to the received bitstream corresponding to thevideo coded data transmission.
 20. A transmitter device apparatus, theapparatus comprising: a transceiver that: receives an indication ofvideo approximate semantic communications mode of a receiver and aconfiguration thereof; and transmits a plurality of video coded datatransmissions; and a processor that uses the configuration of videoapproximate semantic communications mode of the receiver to process HARQfeedback monitoring and to signal for enablement/disablement of semanticerror correction at the receiver.